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Beyond similarity-based methods to associate genes for the inference of function 超越基于相似性的方法来关联基因的功能推断
Biosilico Pub Date : 2003-07-01 DOI: 10.1016/S1478-5382(03)02318-7
John Shon, John Y. Park, Liping Wei
{"title":"Beyond similarity-based methods to associate genes for the inference of function","authors":"John Shon,&nbsp;John Y. Park,&nbsp;Liping Wei","doi":"10.1016/S1478-5382(03)02318-7","DOIUrl":"10.1016/S1478-5382(03)02318-7","url":null,"abstract":"<div><p>The function(s) of a novel gene or gene product can be inferred by associating the gene or gene product with those whose functions are known. It is now common practice to associate two genes if they have similar sequences. In recent years, computational methods have been developed that associate genes on the basis of features beyond similarity, using a variety of biological data beyond single-gene sequences. This review describes several promising methods that associate genes or gene products. These associative methods employ similarity of sequences and structures, features from whole-genome analysis, co-expression patterns from microarray and EST data, interacting properties from proteomic data, and links from literature mining. Finally, we outline issues surrounding the validation and integration of these methods.</p></div>","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 3","pages":"Pages 89-96"},"PeriodicalIF":0.0,"publicationDate":"2003-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02318-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80576230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Predictive in silico models in drug discovery 药物发现中的预测计算机模型
Biosilico Pub Date : 2003-07-01 DOI: 10.1016/S1478-5382(03)02346-1
Christopher Watson
{"title":"Predictive in silico models in drug discovery","authors":"Christopher Watson","doi":"10.1016/S1478-5382(03)02346-1","DOIUrl":"10.1016/S1478-5382(03)02346-1","url":null,"abstract":"","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 3","pages":"Pages 83-84"},"PeriodicalIF":0.0,"publicationDate":"2003-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02346-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78062130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Binformatics: not just for sequences anymore 信息信息学:不再只适用于序列
Biosilico Pub Date : 2003-07-01 DOI: 10.1016/S1478-5382(03)02340-0
Donald G. Jackson , Matthew D. Healy1 , Daniel B. Davison
{"title":"Binformatics: not just for sequences anymore","authors":"Donald G. Jackson ,&nbsp;Matthew D. Healy1 ,&nbsp;Daniel B. Davison","doi":"10.1016/S1478-5382(03)02340-0","DOIUrl":"10.1016/S1478-5382(03)02340-0","url":null,"abstract":"<div><p>The expansion of genomic information has made data integration as important to bioinformatics as computational analyses. A ‘systems biology’ approach to understanding drug targets requires integrating diverse types of data, including nucleotide and protein sequences, mRNA and protein expression measurements, model organism data, alternative splicing, single nucleotide polymorphisms (SNPs) and more. This review describes how publicly available databases and data formats facilitate such integration. However, this discussion is by no means comprehensive. It represents the tools and approaches that Bristol-Myers Squibb (BMS) Bioinformatics has chosen to pursue. At BMS, two tools provide access to this information. Genome browsers provide graphic overviews of sequence-based information, whereas a curated database of drug target information provides annotation and analyses. The integration of all these functions results in a flexible bioinformatics infrastructure for drug discovery.</p></div>","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 3","pages":"Pages 103-111"},"PeriodicalIF":0.0,"publicationDate":"2003-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02340-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86415985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
The future of text mining in genome-based clinical research 基于基因组的临床研究中文本挖掘的未来
Biosilico Pub Date : 2003-07-01 DOI: 10.1016/S1478-5382(03)02336-9
Christian Gieger, Hartwig Deneke, Juliane Fluck
{"title":"The future of text mining in genome-based clinical research","authors":"Christian Gieger,&nbsp;Hartwig Deneke,&nbsp;Juliane Fluck","doi":"10.1016/S1478-5382(03)02336-9","DOIUrl":"10.1016/S1478-5382(03)02336-9","url":null,"abstract":"<div><p>Efficient information retrieval and extraction is a major challenge in molecular biology and genome-based clinical research. In addition, there is an increasing demand to combine information from different resources and across different disciplines in life sciences. Unfortunately, a large proportion of this information is only available in scientific articles. Moreover, the volume of literature is growing almost exponentially. Text mining provides methods to retrieve and extract information contained in free-text automatically. Here, we discuss the challenges and limitations of text mining in biology and medicine, including unsolved problems and necessary developments.</p></div>","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 3","pages":"Pages 97-102"},"PeriodicalIF":0.0,"publicationDate":"2003-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02336-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79257245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
In silico biology and clustered supercomputing: shaping the future of the IT industry 在硅生物学和集群超级计算:塑造IT行业的未来
Biosilico Pub Date : 2003-05-02 DOI: 10.1016/S1478-5382(03)02331-X
Jeff Augen
{"title":"In silico biology and clustered supercomputing: shaping the future of the IT industry","authors":"Jeff Augen","doi":"10.1016/S1478-5382(03)02331-X","DOIUrl":"10.1016/S1478-5382(03)02331-X","url":null,"abstract":"","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 2","pages":"Pages 47-49"},"PeriodicalIF":0.0,"publicationDate":"2003-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02331-X","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84515938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Beyond Moore's law: DNA crystals support computing technologies 超越摩尔定律:DNA晶体支持计算技术
Biosilico Pub Date : 2003-05-02 DOI: 10.1016/S1478-5382(03)02333-3
J.C. Louis (freelance writer)
{"title":"Beyond Moore's law: DNA crystals support computing technologies","authors":"J.C. Louis (freelance writer)","doi":"10.1016/S1478-5382(03)02333-3","DOIUrl":"10.1016/S1478-5382(03)02333-3","url":null,"abstract":"","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 2","pages":"Pages 52-53"},"PeriodicalIF":0.0,"publicationDate":"2003-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02333-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84593693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Finding an oasis in the desert of bioinformatics 在生物信息学的沙漠中找到一片绿洲
Biosilico Pub Date : 2003-05-02 DOI: 10.1016/S1478-5382(03)02327-8
Jeffrey Thomas , David K. Stone
{"title":"Finding an oasis in the desert of bioinformatics","authors":"Jeffrey Thomas ,&nbsp;David K. Stone","doi":"10.1016/S1478-5382(03)02327-8","DOIUrl":"10.1016/S1478-5382(03)02327-8","url":null,"abstract":"","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 2","pages":"Pages 56-58"},"PeriodicalIF":0.0,"publicationDate":"2003-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02327-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72783317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Mining the biomedical literature using semantic analysis and natural language processing techniques 使用语义分析和自然语言处理技术挖掘生物医学文献
Biosilico Pub Date : 2003-05-02 DOI: 10.1016/S1478-5382(03)02330-8
Ronen Feldman , Yizhar Regev , Eyal Hurvitz , Michal Finkelstein-Landau
{"title":"Mining the biomedical literature using semantic analysis and natural language processing techniques","authors":"Ronen Feldman ,&nbsp;Yizhar Regev ,&nbsp;Eyal Hurvitz ,&nbsp;Michal Finkelstein-Landau","doi":"10.1016/S1478-5382(03)02330-8","DOIUrl":"10.1016/S1478-5382(03)02330-8","url":null,"abstract":"<div><p>The information age has made the electronic storage of large amounts of data effortless. The proliferation of documents available on the Internet, corporate intranets, news wires and elsewhere is overwhelming. Search engines only exacerbate this overload problem by making increasingly more documents available in only a few keystrokes. This information overload also exists in the biomedical field, where scientific publications, and other forms of text-based data are produced at an unprecedented rate. Text mining is the combined, automated process of analyzing unstructured, natural language text to discover information and knowledge that are typically difficult to retrieve. Here, we focus on text mining as applied to the biomedical literature. We focus in particular on finding relationships among genes, proteins, drugs and diseases, to facilitate an understanding and prediction of complex biological processes. The LitMiner™ system, developed specifically for this purpose; is described in relation to the Knowledge Discovery and Data Mining Cup 2002, which serves as a formal evaluation of the system.</p></div>","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 2","pages":"Pages 69-80"},"PeriodicalIF":0.0,"publicationDate":"2003-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02330-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79040094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 47
Data integration technologies: an unfulfilled revolution in the drug discovery process? 数据集成技术:药物发现过程中尚未实现的革命?
Biosilico Pub Date : 2003-05-02 DOI: 10.1016/S1478-5382(03)03228-1
Brian Donnelly
{"title":"Data integration technologies: an unfulfilled revolution in the drug discovery process?","authors":"Brian Donnelly","doi":"10.1016/S1478-5382(03)03228-1","DOIUrl":"10.1016/S1478-5382(03)03228-1","url":null,"abstract":"<div><p>Successful life science data integration is a complex feat facing today's researchers and bioinformaticians. It demands the seamless access, integration and query of unprecedented amounts of disparate biological data to advance the pace and effectiveness of new drug discovery. This article outlines the current state of technologies available to help achieve this feat. It explores the evolutionary processes that created these challenges, and the underpinnings of several technological innovations working to overcome them. Together, these technologies aim to change the face of drug R&amp;D through an enhanced understanding and interpretation of life sciences data.</p></div>","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 2","pages":"Pages 59-63"},"PeriodicalIF":0.0,"publicationDate":"2003-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)03228-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78084159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Diagnostic signatures from microarrays: a bioinformatics concept for personalized medicine 来自微阵列的诊断签名:个性化医疗的生物信息学概念
Biosilico Pub Date : 2003-05-02 DOI: 10.1016/S1478-5382(03)02329-1
Rainer Spang
{"title":"Diagnostic signatures from microarrays: a bioinformatics concept for personalized medicine","authors":"Rainer Spang","doi":"10.1016/S1478-5382(03)02329-1","DOIUrl":"10.1016/S1478-5382(03)02329-1","url":null,"abstract":"<div><p>Microarrays can be used as diagnostic clinical tools, providing a global overview of gene transcription in diseased tissues. Expression profiles can be easily obtained in a single assay and provide exhaustive information about molecular events that are often directly linked to the cause of a disease. However, the high complexity of the data are challenging. This article reviews recent efforts in bioinformatics and statistics to overcome this problem and make feasible the clinical analysis of gene expression profiles.</p></div>","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":"1 2","pages":"Pages 64-68"},"PeriodicalIF":0.0,"publicationDate":"2003-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02329-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"56572271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 47
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