Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throug...Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems.Mass spectrometry(MS)has emerged as a powerful platform for the annotation and discovery of NPs.MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information.Additionally,the released annotation methodologies,based on a variety of informatics tools,continuously improve the ability to annotate the structure and properties of compounds.This review examines the current mainstream databases and annotation methodologies,focusing on their advantages and limitations.Prospects for future technological advancements are then discussed in terms of novel applications and research objectives.Through a systematic overview,this review aims to provide valuable insights and a reference for MS-based NPs annotation,thereby promoting the discovery of novel natural entities.展开更多
Glaucoma is an eye disease characterized by pathologically elevated intraocular pressure,optic nerve atrophy,and visual field defects,which can lead to irreversible vision loss.In recent years,the rapid development of...Glaucoma is an eye disease characterized by pathologically elevated intraocular pressure,optic nerve atrophy,and visual field defects,which can lead to irreversible vision loss.In recent years,the rapid development of artificial intelligence(AI)technology has provided new approaches for the early diagnosis and management of glaucoma.By classifying and annotating glaucoma-related images,AI models can learn and recognize the specific pathological features of glaucoma,thereby achieving automated imaging analysis and classification.Research on glaucoma imaging classification and annotation mainly involves color fundus photography(CFP),optical coherence tomography(OCT),anterior segment optical coherence tomography(AS-OCT),and ultrasound biomicroscopy(UBM)images.CFP is primarily used for the annotation of the optic cup and disc,while OCT is used for measuring and annotating the thickness of the retinal nerve fiber layer,and AS-OCT and UBM focus on the annotation of the anterior chamber angle structure and the measurement of anterior segment structural parameters.To standardize the classification and annotation of glaucoma images,enhance the quality and consistency of annotated data,and promote the clinical application of intelligent ophthalmology,this guideline has been developed.This guideline systematically elaborates on the principles,methods,processes,and quality control requirements for the classification and annotation of glaucoma images,providing standardized guidance for the classification and annotation of glaucoma images.展开更多
Understanding genetic variant functionality is essential for advancing animal genomics and precision breeding.However,the lack of comprehensive functional genomic annotations in animals limits the effectiveness of mos...Understanding genetic variant functionality is essential for advancing animal genomics and precision breeding.However,the lack of comprehensive functional genomic annotations in animals limits the effectiveness of most variant function assessment methods.In this study,we gather 1030 raw epigenomic datasets from 10 animal species and systematically annotate 7 types of key regulatory regions,creating a comprehensive functional annotation map of animal genomic variants.Our findings demonstrate that integrating variants with regulatory annotations can identify tissues and cell types underlying economic traits,underscoring the utility of these annotations in functional variant discovery.Using our functional annotations,we rank the functional potential of genetic variants and classify over 127 million candidate variants into 5 functional confidence categories,with high-confidence variants significantly enriched in eQTLs and trait-associated SNPs.Incorporating these variants into genomic prediction models can improve estimated breeding value accuracy,demonstrating their practical utility in breeding programs.To facilitate the use of our results,we develop the Integrated Functional Mutation(IFmut:http://www.ifmutants.com:8212)platform,enabling researchers to explore regulatory annotations and assess the functional potential of animal variants efficiently.Our study provides a robust framework for functional genomic annotations in farm animals,enhancing variant function assessment and breeding precision.展开更多
Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summariza...Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summarization is described. Three kernel descriptors such as gradient, shape, and color are extracted, respectively. Feature late-fusion is executed in turn by the multiple kernel learning model to obtain more discriminant image features. Absolute rank and relative rank of the tag-rank model are used to boost the key words＇ weights. A new word integration algorithm named word sequence blocks building （WSBB） is designed to create N-gram word sequences. Sentences are generated according to the N-gram word sequences and predefined templates. Experimental results show that both the BLEU-1 scores and BLEU-2 scores of the sentences are superior to those of the state-of-art baselines.展开更多
It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotat...It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.展开更多
The Chinese tree shrew(Tupaia belangeri chinensis)is emerging as an important experimental animal in multiple fields of biomedical research.Comprehensive reference genome annotation for both mRNA and long non-coding R...The Chinese tree shrew(Tupaia belangeri chinensis)is emerging as an important experimental animal in multiple fields of biomedical research.Comprehensive reference genome annotation for both mRNA and long non-coding RNA(lncRNA)is crucial for developing animal models using this species.In the current study,we collected a total of 234 high-quality RNA sequencing(RNA-seq)datasets and two long-read isoform sequencing(ISO-seq)datasets and improved the annotation of our previously assembled high-quality chromosomelevel tree shrew genome.We obtained a total of 3514 newly annotated coding genes and 50576 lncRNA genes.We also characterized the tissuespecific expression patterns and alternative splicing patterns of mRNAs and lncRNAs and mapped the orthologous relationships among 11 mammalian species using the current annotated genome.We identified 144 tree shrew-specific gene families,including interleukin 6(IL6)and STT3 oligosaccharyltransferase complex catalytic subunit B(STT3B),which underwent significant changes in size.Comparison of the overall expression patterns in tissues and pathways across four species(human,rhesus monkey,tree shrew,and mouse)indicated that tree shrews are more similar to primates than to mice at the tissue-transcriptome level.Notably,the newly annotated purine rich element binding protein A(PURA)gene and the STT3B gene family showed dysregulation upon viral infection.The updated version of the tree shrew genome annotation(KIZ version 3:TS_3.0)is available at http://www.treeshrewdb.org and provides an essential reference for basic and biomedical studies using tree shrew animal models.展开更多
Representing the relationships between ontologies is the key problem of semantic annotations based on multi-ontologies. Traditional approaches only had the ability of denoting the simple concept subsumption relations ...Representing the relationships between ontologies is the key problem of semantic annotations based on multi-ontologies. Traditional approaches only had the ability of denoting the simple concept subsumption relations between ontologies. Through analyzing and classifying the relationships between ontologies, the idea of bridge ontology was proposed, which had the powerful capability of expressing the complex relationships between concepts and relationships between relations in multi-ontologies. Meanwhile, a new approach employing bridge ontology was proposed to deal with the multi-ontologies-based semantic annotation problem. The bridge ontology is a peculiar ontology, which can be created and maintained conveniently, and is effective in the multi-ontologies-based semantic annotation. The approach using bridge ontology has the advantages of low-cost, scalable, robust in the web circumstance, and avoiding the unnecessary ontology extending and integration. Key words semantic web - bridge ontology - multi-ontologies - semantic annotation CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373066, 60303024). National Grand Fundamental Research 973 Program of China (2002CB312000), National Re-search Foundation for the Doctoral Program of Higher Education of China (20020286004)Biography: WANG Peng (1977-), male, Ph.D candidate, research direction: semantic web, ontology, and knowledge representation on the Web.展开更多
Since the publication of this article,the authors have noticed that the GeneIDs from new and original genome annotations don’t match in Table S6,the correct Table S6 is given here.The authors would like to apologize ...Since the publication of this article,the authors have noticed that the GeneIDs from new and original genome annotations don’t match in Table S6,the correct Table S6 is given here.The authors would like to apologize for this error.展开更多
In this paper we propose a novel model ＂recursive directed graph＂ based on feature structure, and apply it to represent the semantic relations of postpositive attributive structures in biomedical texts. The usages o...In this paper we propose a novel model ＂recursive directed graph＂ based on feature structure, and apply it to represent the semantic relations of postpositive attributive structures in biomedical texts. The usages of postpositive attributive are complex and variable, especially three categories： present participle phrase, past participle phrase, and preposition phrase as postpositire attributive, which always bring the difficulties of automatic parsing. We summarize these categories and annotate the semantic information. Compared with dependency structure, feature structure, being recursive directed graph, enhances semantic information extraction in biomedical field. The annotation results show that recursive directed graph is more suitable to extract complex semantic relations for biomedical text mining.展开更多
The abundant entities and entity-attribute relations in medical websites are important data resources for medical research.However,the medical websites are usually characterized of storing entity and attribute values ...The abundant entities and entity-attribute relations in medical websites are important data resources for medical research.However,the medical websites are usually characterized of storing entity and attribute values in different pages.To extract those data records efficiently,we propose an automatic extraction system which is related to entity and attribute relations（attributes and values）of separate storage.Our system includes following modules：（1）rich-information interactive annotation page rendering;（2）separate storage attribute relations annotating;（3）annotated relations for pattern generating and data records extracting.This paper presents the relations about the attributes which are stored in many pages by effective annotation,then generates rules for data records extraction.The experiments show that the system can not only complete attribute relations of separate storage extraction,but also be compatible with regular relation extraction,while maintaining high accuracy.展开更多
基金supported by the National Natural Science Foundation of China(Nos.82274064,82374026,and 82204591)。
文摘Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems.Mass spectrometry(MS)has emerged as a powerful platform for the annotation and discovery of NPs.MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information.Additionally,the released annotation methodologies,based on a variety of informatics tools,continuously improve the ability to annotate the structure and properties of compounds.This review examines the current mainstream databases and annotation methodologies,focusing on their advantages and limitations.Prospects for future technological advancements are then discussed in terms of novel applications and research objectives.Through a systematic overview,this review aims to provide valuable insights and a reference for MS-based NPs annotation,thereby promoting the discovery of novel natural entities.
基金Supported by Guangdong Basic and Applied Basic Research Foundation(No.2025A1515011627)San Ming Project of Medicine in Shenzhen(No.SZSM202311012).
文摘Glaucoma is an eye disease characterized by pathologically elevated intraocular pressure,optic nerve atrophy,and visual field defects,which can lead to irreversible vision loss.In recent years,the rapid development of artificial intelligence(AI)technology has provided new approaches for the early diagnosis and management of glaucoma.By classifying and annotating glaucoma-related images,AI models can learn and recognize the specific pathological features of glaucoma,thereby achieving automated imaging analysis and classification.Research on glaucoma imaging classification and annotation mainly involves color fundus photography(CFP),optical coherence tomography(OCT),anterior segment optical coherence tomography(AS-OCT),and ultrasound biomicroscopy(UBM)images.CFP is primarily used for the annotation of the optic cup and disc,while OCT is used for measuring and annotating the thickness of the retinal nerve fiber layer,and AS-OCT and UBM focus on the annotation of the anterior chamber angle structure and the measurement of anterior segment structural parameters.To standardize the classification and annotation of glaucoma images,enhance the quality and consistency of annotated data,and promote the clinical application of intelligent ophthalmology,this guideline has been developed.This guideline systematically elaborates on the principles,methods,processes,and quality control requirements for the classification and annotation of glaucoma images,providing standardized guidance for the classification and annotation of glaucoma images.
基金supported by the National Natural Science Foundation of China(32341051)the grant from Department of Agriculture and Rural Affairs of Hubei Province(HBZY2023B006-02)+2 种基金the National Funding(2023ZD04050)the National Natural Science Foundation of China Outstanding Youth(32125035)the National Key R&D Young Scientists Project(2022YFD1302000).
文摘Understanding genetic variant functionality is essential for advancing animal genomics and precision breeding.However,the lack of comprehensive functional genomic annotations in animals limits the effectiveness of most variant function assessment methods.In this study,we gather 1030 raw epigenomic datasets from 10 animal species and systematically annotate 7 types of key regulatory regions,creating a comprehensive functional annotation map of animal genomic variants.Our findings demonstrate that integrating variants with regulatory annotations can identify tissues and cell types underlying economic traits,underscoring the utility of these annotations in functional variant discovery.Using our functional annotations,we rank the functional potential of genetic variants and classify over 127 million candidate variants into 5 functional confidence categories,with high-confidence variants significantly enriched in eQTLs and trait-associated SNPs.Incorporating these variants into genomic prediction models can improve estimated breeding value accuracy,demonstrating their practical utility in breeding programs.To facilitate the use of our results,we develop the Integrated Functional Mutation(IFmut:http://www.ifmutants.com:8212)platform,enabling researchers to explore regulatory annotations and assess the functional potential of animal variants efficiently.Our study provides a robust framework for functional genomic annotations in farm animals,enhancing variant function assessment and breeding precision.
基金The National Natural Science Foundation of China(No.61133012)the Humanity and Social Science Foundation of the Ministry of Education(No.12YJCZH274)+1 种基金the Humanity and Social Science Foundation of Jiangxi Province(No.XW1502,TQ1503)the Science and Technology Project of Jiangxi Science and Technology Department(No.20121BBG70050,20142BBG70011)
文摘Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summarization is described. Three kernel descriptors such as gradient, shape, and color are extracted, respectively. Feature late-fusion is executed in turn by the multiple kernel learning model to obtain more discriminant image features. Absolute rank and relative rank of the tag-rank model are used to boost the key words＇ weights. A new word integration algorithm named word sequence blocks building （WSBB） is designed to create N-gram word sequences. Sentences are generated according to the N-gram word sequences and predefined templates. Experimental results show that both the BLEU-1 scores and BLEU-2 scores of the sentences are superior to those of the state-of-art baselines.
基金the support of the National Natural Science Foundation of China under Grant No.60673023,60433020,10501017,3040016the European Commission for TH/Asia Link/010 under Grant No.111084.
文摘It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.
基金This study was supported by the National Natural Science Foundation of China(U1902215 to Y.G.Y.and 31970542 to Y.F.)Chinese Academy of Sciences(Light of West China Program xbzg-zdsys-201909 to Y.G.Y.)Yunnan Province(202001AS070023 and 2018FB046 to D.D.Y.and 202002AA100007 to Y.G.Y.)。
文摘The Chinese tree shrew(Tupaia belangeri chinensis)is emerging as an important experimental animal in multiple fields of biomedical research.Comprehensive reference genome annotation for both mRNA and long non-coding RNA(lncRNA)is crucial for developing animal models using this species.In the current study,we collected a total of 234 high-quality RNA sequencing(RNA-seq)datasets and two long-read isoform sequencing(ISO-seq)datasets and improved the annotation of our previously assembled high-quality chromosomelevel tree shrew genome.We obtained a total of 3514 newly annotated coding genes and 50576 lncRNA genes.We also characterized the tissuespecific expression patterns and alternative splicing patterns of mRNAs and lncRNAs and mapped the orthologous relationships among 11 mammalian species using the current annotated genome.We identified 144 tree shrew-specific gene families,including interleukin 6(IL6)and STT3 oligosaccharyltransferase complex catalytic subunit B(STT3B),which underwent significant changes in size.Comparison of the overall expression patterns in tissues and pathways across four species(human,rhesus monkey,tree shrew,and mouse)indicated that tree shrews are more similar to primates than to mice at the tissue-transcriptome level.Notably,the newly annotated purine rich element binding protein A(PURA)gene and the STT3B gene family showed dysregulation upon viral infection.The updated version of the tree shrew genome annotation(KIZ version 3:TS_3.0)is available at http://www.treeshrewdb.org and provides an essential reference for basic and biomedical studies using tree shrew animal models.
文摘Representing the relationships between ontologies is the key problem of semantic annotations based on multi-ontologies. Traditional approaches only had the ability of denoting the simple concept subsumption relations between ontologies. Through analyzing and classifying the relationships between ontologies, the idea of bridge ontology was proposed, which had the powerful capability of expressing the complex relationships between concepts and relationships between relations in multi-ontologies. Meanwhile, a new approach employing bridge ontology was proposed to deal with the multi-ontologies-based semantic annotation problem. The bridge ontology is a peculiar ontology, which can be created and maintained conveniently, and is effective in the multi-ontologies-based semantic annotation. The approach using bridge ontology has the advantages of low-cost, scalable, robust in the web circumstance, and avoiding the unnecessary ontology extending and integration. Key words semantic web - bridge ontology - multi-ontologies - semantic annotation CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373066, 60303024). National Grand Fundamental Research 973 Program of China (2002CB312000), National Re-search Foundation for the Doctoral Program of Higher Education of China (20020286004)Biography: WANG Peng (1977-), male, Ph.D candidate, research direction: semantic web, ontology, and knowledge representation on the Web.
文摘Since the publication of this article,the authors have noticed that the GeneIDs from new and original genome annotations don’t match in Table S6,the correct Table S6 is given here.The authors would like to apologize for this error.
基金Supported by the National Natural Science Foundation of China(61202193,61202304)the Major Projects of Chinese National Social Science Foundation(11&ZD189)the Chinese Postdoctoral Science Foundation(2013M540593,2014T70722)
文摘In this paper we propose a novel model ＂recursive directed graph＂ based on feature structure, and apply it to represent the semantic relations of postpositive attributive structures in biomedical texts. The usages of postpositive attributive are complex and variable, especially three categories： present participle phrase, past participle phrase, and preposition phrase as postpositire attributive, which always bring the difficulties of automatic parsing. We summarize these categories and annotate the semantic information. Compared with dependency structure, feature structure, being recursive directed graph, enhances semantic information extraction in biomedical field. The annotation results show that recursive directed graph is more suitable to extract complex semantic relations for biomedical text mining.
基金Supported by the Natural Science Foundation of Hubei Province(2013CFB334)
文摘The abundant entities and entity-attribute relations in medical websites are important data resources for medical research.However,the medical websites are usually characterized of storing entity and attribute values in different pages.To extract those data records efficiently,we propose an automatic extraction system which is related to entity and attribute relations（attributes and values）of separate storage.Our system includes following modules：（1）rich-information interactive annotation page rendering;（2）separate storage attribute relations annotating;（3）annotated relations for pattern generating and data records extracting.This paper presents the relations about the attributes which are stored in many pages by effective annotation,then generates rules for data records extraction.The experiments show that the system can not only complete attribute relations of separate storage extraction,but also be compatible with regular relation extraction,while maintaining high accuracy.
