Handbook of Research on Computational and Systems Biology最新文献_第3页

Addressing the Challenges of Detecting Epistasis in Genome-Wide Association Studies of Common Human Diseases Using Biological Expert Knowledge 利用生物学专家知识解决人类常见疾病全基因组关联研究中检测上位性的挑战

Handbook of Research on Computational and Systems Biology Pub Date : 1900-01-01 DOI: 10.4018/978-1-60960-491-2.ch006

K. Pattin, J. Moore

{"title":"Addressing the Challenges of Detecting Epistasis in Genome-Wide Association Studies of Common Human Diseases Using Biological Expert Knowledge","authors":"K. Pattin, J. Moore","doi":"10.4018/978-1-60960-491-2.ch006","DOIUrl":"https://doi.org/10.4018/978-1-60960-491-2.ch006","url":null,"abstract":"Recent technological developments in the field of genetics have given rise to an abundance of research tools, such as genome-wide genotyping, that allow researchers to conduct genome-wide association studies (GWAS) for detecting genetic variants that confer increased or decreased susceptibility to disease. However, discovering epistatic, or gene-gene, interactions in high dimensional datasets is a problem due to the computational complexity that results from the analysis of all possible combinations of singlenucleotide polymorphisms (SNPs). A recently explored approach to this problem employs biological expert knowledge, such as pathway or protein-protein interaction information, to guide an analysis by the selection or weighting of SNPs based on this knowledge. Narrowing the evaluation to gene combinations that have been shown to interact experimentally provides a biologically concise reason why those two genes may be detected together statistically. This chapter discusses the challenges of discovering epistatic interactions in GWAS and how biological expert knowledge can be used to facilitate genomewide genetic studies.","PeriodicalId":254251,"journal":{"name":"Handbook of Research on Computational and Systems Biology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134361416","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: 4

Using Systems Biology Approaches to Predict New Players in the Innate Immune System 使用系统生物学方法来预测先天免疫系统中的新参与者

Handbook of Research on Computational and Systems Biology Pub Date : 1900-01-01 DOI: 10.4018/978-1-60960-491-2.ch020

Bin Li

{"title":"Using Systems Biology Approaches to Predict New Players in the Innate Immune System","authors":"Bin Li","doi":"10.4018/978-1-60960-491-2.ch020","DOIUrl":"https://doi.org/10.4018/978-1-60960-491-2.ch020","url":null,"abstract":"Toll-like receptors (TLRs) are critical players in the innate immune response to pathogens. However, transcriptional regulatory mechanisms in the TLR activation pathways are still relatively poorly characterized. To address this question, the author of this chapter applied a systematic approach to predict transcription factors that temporally regulate differentially expressed genes under diverse TLR stimuli. Time-course microarray data were selected from mouse bone marrow-derived macrophages stimulated by six TLR agonists. Differentially regulated genes were clustered on the basis of their dynamic behavior. The author then developed a computational method to identify positional overlapping transcription factor (TF) binding sites in each cluster, so as to predict possible TFs that may regulate these genes. A second microarray dataset, on wild-type, Myd88-/and Trif-/macrophages stimulated by lipopolysaccharide (LPS), was used to provide supporting evidence on this combined approach. Overall, the author was able to identify known TLR TFs, as well as to predict new TFs that may be involved in TLR signaling. DOI: 10.4018/978-1-4666-3604-0.ch037","PeriodicalId":254251,"journal":{"name":"Handbook of Research on Computational and Systems Biology","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125175163","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: 8

Cancer and Signaling Pathway Deregulation 癌症和信号通路放松管制

Handbook of Research on Computational and Systems Biology Pub Date : 1900-01-01 DOI: 10.4018/978-1-60960-491-2.ch017

Yingchun Liu

引用次数: 0

Systems Biology-Based Approaches Applied to Vaccine Development 基于系统生物学的方法在疫苗开发中的应用

Handbook of Research on Computational and Systems Biology Pub Date : 1900-01-01 DOI: 10.4018/978-1-4666-2455-9.CH058

P. Manque, Ute Woehlbier

{"title":"Systems Biology-Based Approaches Applied to Vaccine Development","authors":"P. Manque, Ute Woehlbier","doi":"10.4018/978-1-4666-2455-9.CH058","DOIUrl":"https://doi.org/10.4018/978-1-4666-2455-9.CH058","url":null,"abstract":"Vaccines represent one of the most cost-effective ways to prevent and treat diseases. The use of vaccines in the control of viral diseases represents an important milestone in the history of medicine. The genomic revolution brought us the possibility to scan genomes in the search of new and more effective vaccine candidates and the advancement of bioinformatics provided the framework for the application of strategies that were focused not only on antigen discovery but also on comparative genomics, and pathogenic factor identification and data mining. In addition, the progress in post-genomic technologies including gene expression technologies such as microarray and proteomics gave us the opportunity to explore the host responses to vaccines leading to a better understanding of immune responses to pathogens and/or to vaccines, assisting in the development of new and better vaccines and adjuvants. This chapter will review how systems biology-based approaches including genomics, gene expression technologies, and bioinformatics have changed the way of thinking about antigen discovery and vaccine development. In addition, the chapter will discuss how the study of the host responses in combination with “in silico” approaches could help predict immunogenicity and improve the efficacy of vaccines.","PeriodicalId":254251,"journal":{"name":"Handbook of Research on Computational and Systems Biology","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117055673","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

Prediction of Epigenetic Target Sites by Using Genomic DNA Sequence 利用基因组DNA序列预测表观遗传靶点

Handbook of Research on Computational and Systems Biology Pub Date : 1900-01-01 DOI: 10.4018/978-1-60960-491-2.ch008

Guocheng Yuan

引用次数: 7