This study aimed to evaluate the correlation between nursing informatics(NI)competency and information literacy skills for evidencebased practice(EBP)among intensive care nurses.This cross-sectional study was conducte...This study aimed to evaluate the correlation between nursing informatics(NI)competency and information literacy skills for evidencebased practice(EBP)among intensive care nurses.This cross-sectional study was conducted on 184 nurses working in intensive care units(ICUs).The study data were collected through demographic information,Nursing Informatics Competency Assessment Tool(NICAT),and information literacy skills for EBP questionnaires.The intensive care nurses received competent and low-moderate levels for the total scores of NI competency and information literacy skills,respectively.They received a moderate score for the use of different information resources but a low score for information searching skills,different search features,and knowledge about search operators,and only 31.5%of the nurses selected the most appropriate statement.NI competency and related subscales had a significant direct bidirectional correlation with information literacy skills for EBP and its subscales(P<0.05).Nurses require a high level of NI competency and information literacy for EBP to obtain up-to-date information and provide better care and decision-making.Health planners and policymakers should develop interventions to enhance NI competency and information literacy skills among nurses and motivate them to use EBP in clinical settings.展开更多
Quantum information processing and communication(QIPC) is an area of science that has two main goals: On one side,it tries to explore(still not well known) potential of quantum phenomena for(efficient and reliable) in...Quantum information processing and communication(QIPC) is an area of science that has two main goals: On one side,it tries to explore(still not well known) potential of quantum phenomena for(efficient and reliable) information processing and(efficient,reliable and secure) communication.On the other side,it tries to use quantum information storing,processing and transmitting paradigms,principles,laws,limitations,concepts,models and tools to get deeper insights into the phenomena of quantum world and to find efficient ways to describe and handle/simulate various complex physical phenomena.In order to do that QIPC has to use concepts,models,theories,methods and tools of both physics and informatics.The main role of physics at that is to discover primitive physical phenomena that can be used to design and maintain complex and reliable information storing,processing and transmitting systems.The main role of informatics is,one one side,to explore,from the information processing and communication point of view,limitations and potentials of the potential quantum information processing and communication technology,and to prepare information processing methods that could utilise potential of quantum information processing and communication technologies.On the other side,the main role of informatics is to guide and support,by theoretical tools and outcomes,physics oriented research in QIPC.The paper is to describe and analyse a variety of ways and potential informatics contributes and should/could contribute to the development of QIPC--see also Gruska(1999,2006,2008).展开更多
Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-ins...Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-inspired computation,and the Internet of Medical Things.It has helped in knowledge sharing and scaling ability between patients,doctors,and clinics for effective treatment of patients.Speech-based respiratory disease detection and monitoring are crucial in this direction and have shown several promising results.Since the subject’s speech can be remotely recorded and submitted for further examination,it offers a quick,economical,dependable,and noninvasive prospective alternative detection approach.However,the two main requirements of this are higher accuracy and lower computational complexity and,in many cases,these two requirements do not correlate with each other.This problem has been taken up in this paper to develop a low computational complexity-based neural network with higher accuracy.A cascaded perceptual functional link artificial neural network(PFLANN)is used to capture the nonlinearity in the data for better classification performance with low computational complexity.The proposed model is being tested for multiple respiratory diseases,and the analysis of various performance matrices demonstrates the superior performance of the proposed model both in terms of accuracy and complexity.展开更多
Bovine coronavirus(BCoV)poses a significant threat to the global cattle industry,causing both respiratory and gastrointestinal infections in cattle populations.This necessitates the development of efficacious vaccines...Bovine coronavirus(BCoV)poses a significant threat to the global cattle industry,causing both respiratory and gastrointestinal infections in cattle populations.This necessitates the development of efficacious vaccines.While several inactivated and live BCoV vaccines exist,they are predominantly limited to calves.The immunization of adult cattle is imperative for BCoV infection control,as it curtails viral transmission to calves and ameliorates the impact of enteric and respiratory ailments across all age groups within the herd.This study presents an in silico methodology for devising a multiepitope vaccine targeting BCoV.The spike glycoprotein(S)and nucleocapsid(N)proteins,which are integral elements of the BCoV structure,play pivotal roles in the viral infection cycle and immune response.We constructed a remarkably effective multiepitope vaccine candidate specifically designed to combat the BCoV population.Using immunoinformatics technology,B-cell and T-cell epitopes were predicted and linked together using linkers and adjuvants to efficiently trigger both cellular and humoral immune responses in cattle.The in silico construct was characterized,and assessment of its physicochemical properties revealed the formation of a stable vaccine construct.After 3D modeling of the vaccine construct,molecular docking revealed a stable interaction with the bovine receptor bTLR4.Moreover,the viability of the vaccine’s high expression and simple purification was demonstrated by codon optimization and in silico cloning expression into the pET28a(+)vector.By applying immunoinformatics approaches,researchers aim to better understand the immune response to bovine coronavirus,discover potential targets for intervention,and facilitate the development of diagnostic tools and vaccines to mitigate the impact of this virus on cattle health and the livestock industry.We anticipate that the design will be useful as a preventive treatment for BCoV sickness in cattle,opening the door for further laboratory studies.展开更多
There are quintillions of data on deoxyribonucleic acid(DNA)and protein in publicly accessible data banks,and that number is expanding at an exponential rate.Many scientific fields,such as bioinformatics and drug disc...There are quintillions of data on deoxyribonucleic acid(DNA)and protein in publicly accessible data banks,and that number is expanding at an exponential rate.Many scientific fields,such as bioinformatics and drug discovery,rely on such data;nevertheless,gathering and extracting data from these resources is a tough undertaking.This data should go through several processes,including mining,data processing,analysis,and classification.This study proposes software that extracts data from big data repositories automatically and with the particular ability to repeat data extraction phases as many times as needed without human intervention.This software simulates the extraction of data from web-based(point-and-click)resources or graphical user interfaces that cannot be accessed using command-line tools.The software was evaluated by creating a novel database of 34 parameters for 1360 physicochemical properties of antimicrobial peptides(AMP)sequences(46240 hits)from various MARVIN software panels,which can be later utilized to develop novel AMPs.Furthermore,for machine learning research,the program was validated by extracting 10,000 protein tertiary structures from the Protein Data Bank.As a result,data collection from the web will become faster and less expensive,with no need for manual data extraction.The software is critical as a first step to preparing large datasets for subsequent stages of analysis,such as those using machine and deep-learning applications.展开更多
The liver is a multifaceted organ that is responsible for many critical functions encompassing amino acid,carbohydrate,and lipid metabolism,all of which make a healthy liver essential for the human body.Contemporary i...The liver is a multifaceted organ that is responsible for many critical functions encompassing amino acid,carbohydrate,and lipid metabolism,all of which make a healthy liver essential for the human body.Contemporary imaging methodologies have remarkable diagnostic accuracy in discerning focal liver lesions;however,a comprehensive understanding of diffuse liver diseases is a requisite for radiologists to accurately diagnose or predict the progression of such lesions within clinical contexts.Nonetheless,the conventional attributes of radiological features,including morphology,size,margin,density,signal intensity,and echoes,limit their clinical utility.Radiomics is a widely used approach that is characterized by the extraction of copious image features from radiographic depictions,which gives it considerable potential in addressing this limitation.It is worth noting that functional or molecular alterations occur significantly prior to the morphological shifts discernible by imaging modalities.Consequently,the explication of potential mechanisms by multiomics analyses(encompassing genomics,epigenomics,transcriptomics,proteomics,and metabolomics)is essential for investigating putative signal pathway regulations from a radiological viewpoint.In this review,we elaborate on the principal pathological categorizations of diffuse liver diseases,the evaluation of multiomics approaches pertaining to diffuse liver diseases,and the prospective value of predictive models.Accordingly,the overarching objective of this review is to scrutinize the interrelations between radiological features and bioinformatics as well as to consider the development of prediction models predicated on radiobioinformatics as integral components of clinical decision support systems for diffuse liver diseases.展开更多
Severe acute respiratory syndrome coronavirus(SARS-CoV)and SARS-CoV-2 are thought to transmit to humans via wild mammals,especially bats.However,evidence for direct bat-to-human transmission is lacking.Involvement of ...Severe acute respiratory syndrome coronavirus(SARS-CoV)and SARS-CoV-2 are thought to transmit to humans via wild mammals,especially bats.However,evidence for direct bat-to-human transmission is lacking.Involvement of intermediate hosts is considered a reason for SARS-CoV-2 transmission to humans and emergence of outbreak.Large biodiversity is found in tropical territories,such as Brazil.On the similar line,this study aimed to predict potential coronavirus hosts among Brazilian wild mammals based on angiotensin-converting enzyme 2(ACE2)sequences using evolutionary bioinformatics.Cougar,maned wolf,and bush dogs were predicted as potential hosts for coronavirus.These indigenous carnivores are philogenetically closer to the known SARS-CoV/SARS-CoV-2 hosts and presented low ACE2 divergence.A new coronavirus transmission chain was developed in which white-tailed deer,a susceptible SARS-CoV-2 host,have the central position.Cougar play an important role because of its low divergent ACE2 level in deer and humans.The discovery of these potential coronavirus hosts will be useful for epidemiological surveillance and discovery of interventions that can contribute to break the transmission chain.展开更多
Multidisciplinary, integrated planning approach by architects, engineers, scientists and manufacturers to reduce energy consumption of buildings. The CIIRC Complex, located on the main campus of Czech Technical Univer...Multidisciplinary, integrated planning approach by architects, engineers, scientists and manufacturers to reduce energy consumption of buildings. The CIIRC Complex, located on the main campus of Czech Technical University in Prague consists of two buildings, newly constructed building and adaptive reuse of existing building. CIIRC—Czech Institute of Informatics, Robotics and Cybernetics is a contemporary teaching facility of new generation and use for scientific research teams. New building has ten above-ground floors, on the bottom 4 floors of laboratories, scientist modules, classrooms, above are offices, meeting rooms, teaching and research modules for professors and students. Offices of the rector are on the last two floors of the building. On the top floor is congress type auditorium, in the basement is fully automatic car park. Double skin pneumatic cushions facade. In the project are introduced series of architectural and technical features and innovations. Probably the most visible is the double skin facade facing south-transparent double layer membrane ETFE (Ethylen-TetraFluorEthylen) cushions with triple glazed modular system assembly. Acting as solar collector, recuperating of hot air on the top floors, saving up to 30% of an energy consumption.展开更多
Bioinformatics analysis often requires the filtering of multi-datasets,based on frequency or frequency of occurrence,for decisions on retention or deletion.Existing tools for this purpose often present a challenge wit...Bioinformatics analysis often requires the filtering of multi-datasets,based on frequency or frequency of occurrence,for decisions on retention or deletion.Existing tools for this purpose often present a challenge with complex installation,which necessitate custom coding,thereby impeding efficient data processing activities.To address this issue,Filterx,a user-friendly command line tool that written in C language,was developed that supports multi-condition filtering,based on frequency or occurrence.This tool enables users to complete the data processing tasks through a simple command line,greatly reducing both workload and data processing time.In addition,future development of this tool could facilitate its integration into various bioinformatics data analysis pipelines.展开更多
Parkinson’s disease(PD)is a common neurological disease in elderly people,and its morbidity and mortality are increasing with the advent of global ageing.The traditional paradigm of moving from small data to big data...Parkinson’s disease(PD)is a common neurological disease in elderly people,and its morbidity and mortality are increasing with the advent of global ageing.The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations.To highlight the use of big data for precision PD medicine,we review PD big data and informatics for the translation of basic PD research to clinical applications.We emphasize some key findings in clinically actionable changes,such as susceptibility genetic variations for PD risk population screening,biomarkers for the diagnosis and stratification of PD patients,risk factors for PD,and lifestyles for the prevention of PD.The challenges associated with the collection,storage,and modelling of diverse big data for PD precision medicine and healthcare are also summarized.Future perspectives on systems modelling and intelligent medicine for PD monitoring,diagnosis,treatment,and healthcare are discussed in the end.展开更多
Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown...Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown.For this purpose,here we present a genomic location based bioinformatics method to predict the lncRNAs associated with vascular disease.We applied the presented method to globally screen the human lncRNAs potentially involved in vascular disease.As a result,we predicted 3043 putative vascular disease associated lncRNAs.To test the accuracy of the method,we selected 10 lncRNAs predicted to be implicated in proliferation and migration of vascular smooth muscle cells(VSMCs)for further experimental validation.The results confirmed that eight of the 10 lncRNAs(80%)are validated.This result suggests that the presented method has a reliable prediction performance.Finally,the presented bioinformatics method and the predicted vascular disease associated lncRNAs together may provide helps for not only better understanding of the roles of lncRNAs in vascular disease but also the identification of novel molecules for the diagnosis and therapy of vascular disease.展开更多
We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database（YPED） that is used by investigators at more than 300 institutions worldwide. YPED ...We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database（YPED） that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a singlelaboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry（LC–MS/MS） database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring（MRM）/selective reaction monitoring（SRM） assay development. We have linked YPED＇s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.展开更多
The explosive growth of the bioinformatics field has led to a large amount of data and software applications publicly available as web resources. However, the lack of persistence of web references is a barrier to a co...The explosive growth of the bioinformatics field has led to a large amount of data and software applications publicly available as web resources. However, the lack of persistence of web references is a barrier to a comprehensive shared access. We conducted a study of the current availability and other features of primary bioinforo matics web resources （such as software tools and databases）. The majority （95%） of the examined bioinformatics web resources were found running on UNIX/Linux operating systems, and the most widely used web server was found to be Apache （or Apache-related products）. Of the overall 1,130 Uniform Resource Locators （URLs） examined, 91% were highly available （more than 90% of the time）, while only 4% showed low accessibility （less than 50% of the time） during the survey. Furthermore, the most common URL failure modes are presented and analyzed.展开更多
Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other...Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.展开更多
Alzheimer’s disease(AD)is the most common form of dementia,affecting over 50 million people worldwide.This figure is projected to nearly double every 20 years,reaching 82 million by 2030 and 152 million by 2050(Alzhe...Alzheimer’s disease(AD)is the most common form of dementia,affecting over 50 million people worldwide.This figure is projected to nearly double every 20 years,reaching 82 million by 2030 and 152 million by 2050(Alzheimer’s Disease International).The apolipoproteinε4(APOE4)allele is the strongest genetic risk factor for late-onset AD(after age 65 years).Apolipoprotein E,a lipid transporter,exists in three variants:ε2,ε3,andε4.APOEε2(APOE2)is protective against AD,APOEε3(APOE3)is neutral,while APOE4 significantly increases the risk.Individuals with one copy of APOE4 have a 4-fold greater risk of developing AD,and those with two copies face an 8-fold risk compared to non-carriers.Even in cognitively normal individuals,APOE4 carriers exhibit brain metabolic and vascular deficits decades before amyloid-beta(Aβ)plaques and neurofibrillary tau tangles emerge-the hallmark pathologies of AD(Reiman et al.,2001,2005;Thambisetty et al.,2010).Notably,studies have demonstrated reduced glucose uptake,or hypometabolism,in brain regions vulnerable to AD in asymptomatic middle-aged APOE4 carriers,long before clinical symptoms arise(Reiman et al.,2001,2005).展开更多
Precision medicine advocates for the practice of customized disease treatment and prevention such that all clinical decisions are made based on the characteristics of individual patients. The precision medicine framew...Precision medicine advocates for the practice of customized disease treatment and prevention such that all clinical decisions are made based on the characteristics of individual patients. The precision medicine framework has been enthusiastically endorsed by the health care community and is set to have a profound impact on the health care practice. However, adopting the precision medicine ideology in the clinics requires solving a series of technical challenges, particularly in informatics and data analytics. To better serve this newly emerging area of research, we present this special issue to showcase the latest research developments in bioinformatics which has been widely regarded as a major stakeholder in the advancement of precision medicine. The ten papers appear in special collection cover a wide range of topics and can be broadly categorized into the following three main areas： statistical method development; informatics method development and algorithms for translational bioinformatics.展开更多
Genomics and proteomics have emerged as key technologies in biomedical research, resulting in a surge of interest in training by investigators keen to incorporate these technologies into their research. At least two t...Genomics and proteomics have emerged as key technologies in biomedical research, resulting in a surge of interest in training by investigators keen to incorporate these technologies into their research. At least two types of training can be envisioned in order to produce meaningful results, quality publications and successful grant applications： （1） immediate short-term training workshops and （2） long-term graduate education or visiting scientist programs. We aimed to fill the former need by providing a comprehensive hands-on training course in genomics, proteomics and informatics in a coherent, experimentally-based framework. This was accomplished through a National Heart, Lung, and Blood Institute （NHLBI）-sponsored 10-day Genomics and Proteomics Hands-on Workshop held at National Jewish Health （NJH） and the University of Colorado School of Medicine （UCD）. The course content included comprehensive lectures and laboratories in mass spectrometry and genomics technologies, extensive hands-on experience with instrumentation and software, video demonstrations, optional workshops, online sessions, invited keynote speakers, and local and national vip faculty. Here we describe the detailed curriculum and present the results of short- and long-term evaluations from course attendees. Our educational program consis- tently received positive reviews from participants and had a substantial impact on grant writing and review, manuscript submissions and publications.展开更多
Chromatin immunoprecipitation sequencing(Ch IP-seq)and the Assay for Transposase-Accessible Chromatin with high-throughput sequencing(ATAC-seq)have become essential technologies to effectively measure protein–DNA int...Chromatin immunoprecipitation sequencing(Ch IP-seq)and the Assay for Transposase-Accessible Chromatin with high-throughput sequencing(ATAC-seq)have become essential technologies to effectively measure protein–DNA interactions and chromatin accessibility.However,there is a need for a scalable and reproducible pipeline that incorporates proper normalization between samples,correction of copy number variations,and integration of new downstream analysis tools.Here we present Containerized Bioinformatics workflow for Reproducible Ch IP/ATAC-seq Analysis(Co BRA),a modularized computational workflow which quantifies Ch IP-seq and ATAC-seq peak regions and performs unsupervised and supervised analyses.Co BRA provides a comprehensive state-of-the-art Ch IP-seq and ATAC-seq analysis pipeline that can be used by scientists with limited computational experience.This enables researchers to gain rapid insight into protein–DNA interactions and chromatin accessibility through sample clustering,differential peak calling,motif enrichment,comparison of sites to a reference database,and pathway analysis.Co BRA is publicly available online at https://bitbucket.org/cfce/cobra.展开更多
Dear Editor,Oryza sativa subsp, indica and japonica are two subspecies of Asian cultivated rice, among which indica rice is much more widely grown and genetically diverse. Over the past years, the Rice Annotation Proj...Dear Editor,Oryza sativa subsp, indica and japonica are two subspecies of Asian cultivated rice, among which indica rice is much more widely grown and genetically diverse. Over the past years, the Rice Annotation Project Database （RAP-DB） （Ohyanagi et al., 2006） and Michigan State University Rice Genome Annotation Project （MSU-RGAP） （Ouyang et al., 2007） are two popular databases that have been developed to manage rice genomic and transcriptomic data based on the unified reference genome of japonica cultivar Nipponbare （International Rice Genome Sequencing Project, 2005）. Beijing Genomics Institute Rice Information System （BGI-RIS） （Zhao et ai., 2004） is an available resource for indica rice cultivar 93-11;展开更多
Obesity is a major risk factor for chronic diseases,underscoring the need for early diagnosis and effective management.This study presents a novel expert system designed to accurately classify obesity levels and provi...Obesity is a major risk factor for chronic diseases,underscoring the need for early diagnosis and effective management.This study presents a novel expert system designed to accurately classify obesity levels and provide personalised treatment recommendations.Five machine learning algorithms—decision tree,random forest,multinomial logistic regression(MLR),Naive Bayes,and support vector machine(SVM)—were evaluated using the SEMMA data mining methodology and the tidymodels framework.MLR demonstrated the highest accuracy(97.48%)and was selected as the final model.The system features a userfriendly interface built with R Shiny,facilitating real-time interaction and a seamless user experience.Treatment recommendations are generated through if-then rule-based logic,ensuring tailored guidance for each obesity category.Comparative analysis highlights the system's superior diagnostic accuracy and practical application in treatment guidance.Its accessibility,particularly in underserved rural populations,enhances public health outcomes by enabling early diagnosis,targeted interventions,and proactive obesity management.展开更多
文摘This study aimed to evaluate the correlation between nursing informatics(NI)competency and information literacy skills for evidencebased practice(EBP)among intensive care nurses.This cross-sectional study was conducted on 184 nurses working in intensive care units(ICUs).The study data were collected through demographic information,Nursing Informatics Competency Assessment Tool(NICAT),and information literacy skills for EBP questionnaires.The intensive care nurses received competent and low-moderate levels for the total scores of NI competency and information literacy skills,respectively.They received a moderate score for the use of different information resources but a low score for information searching skills,different search features,and knowledge about search operators,and only 31.5%of the nurses selected the most appropriate statement.NI competency and related subscales had a significant direct bidirectional correlation with information literacy skills for EBP and its subscales(P<0.05).Nurses require a high level of NI competency and information literacy for EBP to obtain up-to-date information and provide better care and decision-making.Health planners and policymakers should develop interventions to enhance NI competency and information literacy skills among nurses and motivate them to use EBP in clinical settings.
基金Support of the grant MSM00211622419 is to be acknowledge
文摘Quantum information processing and communication(QIPC) is an area of science that has two main goals: On one side,it tries to explore(still not well known) potential of quantum phenomena for(efficient and reliable) information processing and(efficient,reliable and secure) communication.On the other side,it tries to use quantum information storing,processing and transmitting paradigms,principles,laws,limitations,concepts,models and tools to get deeper insights into the phenomena of quantum world and to find efficient ways to describe and handle/simulate various complex physical phenomena.In order to do that QIPC has to use concepts,models,theories,methods and tools of both physics and informatics.The main role of physics at that is to discover primitive physical phenomena that can be used to design and maintain complex and reliable information storing,processing and transmitting systems.The main role of informatics is,one one side,to explore,from the information processing and communication point of view,limitations and potentials of the potential quantum information processing and communication technology,and to prepare information processing methods that could utilise potential of quantum information processing and communication technologies.On the other side,the main role of informatics is to guide and support,by theoretical tools and outcomes,physics oriented research in QIPC.The paper is to describe and analyse a variety of ways and potential informatics contributes and should/could contribute to the development of QIPC--see also Gruska(1999,2006,2008).
文摘Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-inspired computation,and the Internet of Medical Things.It has helped in knowledge sharing and scaling ability between patients,doctors,and clinics for effective treatment of patients.Speech-based respiratory disease detection and monitoring are crucial in this direction and have shown several promising results.Since the subject’s speech can be remotely recorded and submitted for further examination,it offers a quick,economical,dependable,and noninvasive prospective alternative detection approach.However,the two main requirements of this are higher accuracy and lower computational complexity and,in many cases,these two requirements do not correlate with each other.This problem has been taken up in this paper to develop a low computational complexity-based neural network with higher accuracy.A cascaded perceptual functional link artificial neural network(PFLANN)is used to capture the nonlinearity in the data for better classification performance with low computational complexity.The proposed model is being tested for multiple respiratory diseases,and the analysis of various performance matrices demonstrates the superior performance of the proposed model both in terms of accuracy and complexity.
文摘Bovine coronavirus(BCoV)poses a significant threat to the global cattle industry,causing both respiratory and gastrointestinal infections in cattle populations.This necessitates the development of efficacious vaccines.While several inactivated and live BCoV vaccines exist,they are predominantly limited to calves.The immunization of adult cattle is imperative for BCoV infection control,as it curtails viral transmission to calves and ameliorates the impact of enteric and respiratory ailments across all age groups within the herd.This study presents an in silico methodology for devising a multiepitope vaccine targeting BCoV.The spike glycoprotein(S)and nucleocapsid(N)proteins,which are integral elements of the BCoV structure,play pivotal roles in the viral infection cycle and immune response.We constructed a remarkably effective multiepitope vaccine candidate specifically designed to combat the BCoV population.Using immunoinformatics technology,B-cell and T-cell epitopes were predicted and linked together using linkers and adjuvants to efficiently trigger both cellular and humoral immune responses in cattle.The in silico construct was characterized,and assessment of its physicochemical properties revealed the formation of a stable vaccine construct.After 3D modeling of the vaccine construct,molecular docking revealed a stable interaction with the bovine receptor bTLR4.Moreover,the viability of the vaccine’s high expression and simple purification was demonstrated by codon optimization and in silico cloning expression into the pET28a(+)vector.By applying immunoinformatics approaches,researchers aim to better understand the immune response to bovine coronavirus,discover potential targets for intervention,and facilitate the development of diagnostic tools and vaccines to mitigate the impact of this virus on cattle health and the livestock industry.We anticipate that the design will be useful as a preventive treatment for BCoV sickness in cattle,opening the door for further laboratory studies.
基金This work was funded by the Graduate Scientific Research School at Yarmouk University under Grant Number:82/2020。
文摘There are quintillions of data on deoxyribonucleic acid(DNA)and protein in publicly accessible data banks,and that number is expanding at an exponential rate.Many scientific fields,such as bioinformatics and drug discovery,rely on such data;nevertheless,gathering and extracting data from these resources is a tough undertaking.This data should go through several processes,including mining,data processing,analysis,and classification.This study proposes software that extracts data from big data repositories automatically and with the particular ability to repeat data extraction phases as many times as needed without human intervention.This software simulates the extraction of data from web-based(point-and-click)resources or graphical user interfaces that cannot be accessed using command-line tools.The software was evaluated by creating a novel database of 34 parameters for 1360 physicochemical properties of antimicrobial peptides(AMP)sequences(46240 hits)from various MARVIN software panels,which can be later utilized to develop novel AMPs.Furthermore,for machine learning research,the program was validated by extracting 10,000 protein tertiary structures from the Protein Data Bank.As a result,data collection from the web will become faster and less expensive,with no need for manual data extraction.The software is critical as a first step to preparing large datasets for subsequent stages of analysis,such as those using machine and deep-learning applications.
基金National Natural Science Foundation of China,Grant/Award Number:81960338Science and Technology Projects of Guizhou Province,Grant/Award Numbers:Qiankehejichu-ZK[2022]422,Qiankehejichu-ZK[2023]353。
文摘The liver is a multifaceted organ that is responsible for many critical functions encompassing amino acid,carbohydrate,and lipid metabolism,all of which make a healthy liver essential for the human body.Contemporary imaging methodologies have remarkable diagnostic accuracy in discerning focal liver lesions;however,a comprehensive understanding of diffuse liver diseases is a requisite for radiologists to accurately diagnose or predict the progression of such lesions within clinical contexts.Nonetheless,the conventional attributes of radiological features,including morphology,size,margin,density,signal intensity,and echoes,limit their clinical utility.Radiomics is a widely used approach that is characterized by the extraction of copious image features from radiographic depictions,which gives it considerable potential in addressing this limitation.It is worth noting that functional or molecular alterations occur significantly prior to the morphological shifts discernible by imaging modalities.Consequently,the explication of potential mechanisms by multiomics analyses(encompassing genomics,epigenomics,transcriptomics,proteomics,and metabolomics)is essential for investigating putative signal pathway regulations from a radiological viewpoint.In this review,we elaborate on the principal pathological categorizations of diffuse liver diseases,the evaluation of multiomics approaches pertaining to diffuse liver diseases,and the prospective value of predictive models.Accordingly,the overarching objective of this review is to scrutinize the interrelations between radiological features and bioinformatics as well as to consider the development of prediction models predicated on radiobioinformatics as integral components of clinical decision support systems for diffuse liver diseases.
文摘Severe acute respiratory syndrome coronavirus(SARS-CoV)and SARS-CoV-2 are thought to transmit to humans via wild mammals,especially bats.However,evidence for direct bat-to-human transmission is lacking.Involvement of intermediate hosts is considered a reason for SARS-CoV-2 transmission to humans and emergence of outbreak.Large biodiversity is found in tropical territories,such as Brazil.On the similar line,this study aimed to predict potential coronavirus hosts among Brazilian wild mammals based on angiotensin-converting enzyme 2(ACE2)sequences using evolutionary bioinformatics.Cougar,maned wolf,and bush dogs were predicted as potential hosts for coronavirus.These indigenous carnivores are philogenetically closer to the known SARS-CoV/SARS-CoV-2 hosts and presented low ACE2 divergence.A new coronavirus transmission chain was developed in which white-tailed deer,a susceptible SARS-CoV-2 host,have the central position.Cougar play an important role because of its low divergent ACE2 level in deer and humans.The discovery of these potential coronavirus hosts will be useful for epidemiological surveillance and discovery of interventions that can contribute to break the transmission chain.
文摘Multidisciplinary, integrated planning approach by architects, engineers, scientists and manufacturers to reduce energy consumption of buildings. The CIIRC Complex, located on the main campus of Czech Technical University in Prague consists of two buildings, newly constructed building and adaptive reuse of existing building. CIIRC—Czech Institute of Informatics, Robotics and Cybernetics is a contemporary teaching facility of new generation and use for scientific research teams. New building has ten above-ground floors, on the bottom 4 floors of laboratories, scientist modules, classrooms, above are offices, meeting rooms, teaching and research modules for professors and students. Offices of the rector are on the last two floors of the building. On the top floor is congress type auditorium, in the basement is fully automatic car park. Double skin pneumatic cushions facade. In the project are introduced series of architectural and technical features and innovations. Probably the most visible is the double skin facade facing south-transparent double layer membrane ETFE (Ethylen-TetraFluorEthylen) cushions with triple glazed modular system assembly. Acting as solar collector, recuperating of hot air on the top floors, saving up to 30% of an energy consumption.
基金supported by grant CNTC-110202101039(JY-16)and YNTC-2022530000241008.
文摘Bioinformatics analysis often requires the filtering of multi-datasets,based on frequency or frequency of occurrence,for decisions on retention or deletion.Existing tools for this purpose often present a challenge with complex installation,which necessitate custom coding,thereby impeding efficient data processing activities.To address this issue,Filterx,a user-friendly command line tool that written in C language,was developed that supports multi-condition filtering,based on frequency or occurrence.This tool enables users to complete the data processing tasks through a simple command line,greatly reducing both workload and data processing time.In addition,future development of this tool could facilitate its integration into various bioinformatics data analysis pipelines.
基金supported by the National Key R&D Program of China(Grant No.2016YFC1306605)the National Natural Science Foundation of China(Grant Nos.31670851,31470821,and 91530320)
文摘Parkinson’s disease(PD)is a common neurological disease in elderly people,and its morbidity and mortality are increasing with the advent of global ageing.The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations.To highlight the use of big data for precision PD medicine,we review PD big data and informatics for the translation of basic PD research to clinical applications.We emphasize some key findings in clinically actionable changes,such as susceptibility genetic variations for PD risk population screening,biomarkers for the diagnosis and stratification of PD patients,risk factors for PD,and lifestyles for the prevention of PD.The challenges associated with the collection,storage,and modelling of diverse big data for PD precision medicine and healthcare are also summarized.Future perspectives on systems modelling and intelligent medicine for PD monitoring,diagnosis,treatment,and healthcare are discussed in the end.
基金supported by the National Natural Science Foundation of China(91339106)National High Technology Research and Development Program of China(2014AA021102)
文摘Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown.For this purpose,here we present a genomic location based bioinformatics method to predict the lncRNAs associated with vascular disease.We applied the presented method to globally screen the human lncRNAs potentially involved in vascular disease.As a result,we predicted 3043 putative vascular disease associated lncRNAs.To test the accuracy of the method,we selected 10 lncRNAs predicted to be implicated in proliferation and migration of vascular smooth muscle cells(VSMCs)for further experimental validation.The results confirmed that eight of the 10 lncRNAs(80%)are validated.This result suggests that the presented method has a reliable prediction performance.Finally,the presented bioinformatics method and the predicted vascular disease associated lncRNAs together may provide helps for not only better understanding of the roles of lncRNAs in vascular disease but also the identification of novel molecules for the diagnosis and therapy of vascular disease.
基金supported in part by the National Institutes of Health of the United States(Grant Nos.UL1 RR024139 to Yale Clinical and Translational Science Award,1S10OD018034-01 to 6500 QTrap Mass Spectrometer for Yale University,1S10RR026707-01 to 5500QTrap Mass Spectrometer for Yale University,P30DA018343 to Yale/NIDA Neuroproteomics Center and NIDDK-K01DK089006 awarded to JR)
文摘We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database（YPED） that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a singlelaboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry（LC–MS/MS） database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring（MRM）/selective reaction monitoring（SRM） assay development. We have linked YPED＇s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.
文摘The explosive growth of the bioinformatics field has led to a large amount of data and software applications publicly available as web resources. However, the lack of persistence of web references is a barrier to a comprehensive shared access. We conducted a study of the current availability and other features of primary bioinforo matics web resources （such as software tools and databases）. The majority （95%） of the examined bioinformatics web resources were found running on UNIX/Linux operating systems, and the most widely used web server was found to be Apache （or Apache-related products）. Of the overall 1,130 Uniform Resource Locators （URLs） examined, 91% were highly available （more than 90% of the time）, while only 4% showed low accessibility （less than 50% of the time） during the survey. Furthermore, the most common URL failure modes are presented and analyzed.
文摘Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.
基金supported by National Institute on Aging(NIH-NIA)R01AG054459(to ALL).
文摘Alzheimer’s disease(AD)is the most common form of dementia,affecting over 50 million people worldwide.This figure is projected to nearly double every 20 years,reaching 82 million by 2030 and 152 million by 2050(Alzheimer’s Disease International).The apolipoproteinε4(APOE4)allele is the strongest genetic risk factor for late-onset AD(after age 65 years).Apolipoprotein E,a lipid transporter,exists in three variants:ε2,ε3,andε4.APOEε2(APOE2)is protective against AD,APOEε3(APOE3)is neutral,while APOE4 significantly increases the risk.Individuals with one copy of APOE4 have a 4-fold greater risk of developing AD,and those with two copies face an 8-fold risk compared to non-carriers.Even in cognitively normal individuals,APOE4 carriers exhibit brain metabolic and vascular deficits decades before amyloid-beta(Aβ)plaques and neurofibrillary tau tangles emerge-the hallmark pathologies of AD(Reiman et al.,2001,2005;Thambisetty et al.,2010).Notably,studies have demonstrated reduced glucose uptake,or hypometabolism,in brain regions vulnerable to AD in asymptomatic middle-aged APOE4 carriers,long before clinical symptoms arise(Reiman et al.,2001,2005).
文摘Precision medicine advocates for the practice of customized disease treatment and prevention such that all clinical decisions are made based on the characteristics of individual patients. The precision medicine framework has been enthusiastically endorsed by the health care community and is set to have a profound impact on the health care practice. However, adopting the precision medicine ideology in the clinics requires solving a series of technical challenges, particularly in informatics and data analytics. To better serve this newly emerging area of research, we present this special issue to showcase the latest research developments in bioinformatics which has been widely regarded as a major stakeholder in the advancement of precision medicine. The ten papers appear in special collection cover a wide range of topics and can be broadly categorized into the following three main areas： statistical method development; informatics method development and algorithms for translational bioinformatics.
基金supported by a grant through the National Institutes of Health,National Heart,Lung,and Blood Institute to Dr.Nichole Reisdorph(Grant No.T15HL086386)
文摘Genomics and proteomics have emerged as key technologies in biomedical research, resulting in a surge of interest in training by investigators keen to incorporate these technologies into their research. At least two types of training can be envisioned in order to produce meaningful results, quality publications and successful grant applications： （1） immediate short-term training workshops and （2） long-term graduate education or visiting scientist programs. We aimed to fill the former need by providing a comprehensive hands-on training course in genomics, proteomics and informatics in a coherent, experimentally-based framework. This was accomplished through a National Heart, Lung, and Blood Institute （NHLBI）-sponsored 10-day Genomics and Proteomics Hands-on Workshop held at National Jewish Health （NJH） and the University of Colorado School of Medicine （UCD）. The course content included comprehensive lectures and laboratories in mass spectrometry and genomics technologies, extensive hands-on experience with instrumentation and software, video demonstrations, optional workshops, online sessions, invited keynote speakers, and local and national vip faculty. Here we describe the detailed curriculum and present the results of short- and long-term evaluations from course attendees. Our educational program consis- tently received positive reviews from participants and had a substantial impact on grant writing and review, manuscript submissions and publications.
基金funding from the National Institutes of Health,United States(Grant Nos.2PO1CA163227 and P01CA250959)。
文摘Chromatin immunoprecipitation sequencing(Ch IP-seq)and the Assay for Transposase-Accessible Chromatin with high-throughput sequencing(ATAC-seq)have become essential technologies to effectively measure protein–DNA interactions and chromatin accessibility.However,there is a need for a scalable and reproducible pipeline that incorporates proper normalization between samples,correction of copy number variations,and integration of new downstream analysis tools.Here we present Containerized Bioinformatics workflow for Reproducible Ch IP/ATAC-seq Analysis(Co BRA),a modularized computational workflow which quantifies Ch IP-seq and ATAC-seq peak regions and performs unsupervised and supervised analyses.Co BRA provides a comprehensive state-of-the-art Ch IP-seq and ATAC-seq analysis pipeline that can be used by scientists with limited computational experience.This enables researchers to gain rapid insight into protein–DNA interactions and chromatin accessibility through sample clustering,differential peak calling,motif enrichment,comparison of sites to a reference database,and pathway analysis.Co BRA is publicly available online at https://bitbucket.org/cfce/cobra.
文摘Dear Editor,Oryza sativa subsp, indica and japonica are two subspecies of Asian cultivated rice, among which indica rice is much more widely grown and genetically diverse. Over the past years, the Rice Annotation Project Database （RAP-DB） （Ohyanagi et al., 2006） and Michigan State University Rice Genome Annotation Project （MSU-RGAP） （Ouyang et al., 2007） are two popular databases that have been developed to manage rice genomic and transcriptomic data based on the unified reference genome of japonica cultivar Nipponbare （International Rice Genome Sequencing Project, 2005）. Beijing Genomics Institute Rice Information System （BGI-RIS） （Zhao et ai., 2004） is an available resource for indica rice cultivar 93-11;
基金supported by the National Research,Development and Innovation Office(NKFIH)(Grant 2024-1.2.3-HU-RIZONT-2024-00030).
文摘Obesity is a major risk factor for chronic diseases,underscoring the need for early diagnosis and effective management.This study presents a novel expert system designed to accurately classify obesity levels and provide personalised treatment recommendations.Five machine learning algorithms—decision tree,random forest,multinomial logistic regression(MLR),Naive Bayes,and support vector machine(SVM)—were evaluated using the SEMMA data mining methodology and the tidymodels framework.MLR demonstrated the highest accuracy(97.48%)and was selected as the final model.The system features a userfriendly interface built with R Shiny,facilitating real-time interaction and a seamless user experience.Treatment recommendations are generated through if-then rule-based logic,ensuring tailored guidance for each obesity category.Comparative analysis highlights the system's superior diagnostic accuracy and practical application in treatment guidance.Its accessibility,particularly in underserved rural populations,enhances public health outcomes by enabling early diagnosis,targeted interventions,and proactive obesity management.
