Predicting Transcription Factor Complexes
In his master thesis Thorsten Will proposes the substantial information content of protein complexes involving transcription factors in the context of gene regulatory networks, designs the first computational approaches to predict such complexes as well as their regulatory function and verifies the practicability using data of the well-studied yeast S.cereviseae. The novel insights offer extensive capabilities towards a better understanding of the combinatorial control driving transcriptional regulation.
Proceedings of the National Academy of Sciences of the United States of America
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Advances in Bioinformatics and Computational Biology
This book constitutes the refereed proceedings of the 7th Brazilian Symposium on Bioinformatics, BSB 2012, held in Campo Grande, Brazil, in August 2012. The 16 regular papers presented were carefully reviewed and selected for inclusion in this book. It also contains a joint paper from two of the guest speakers. The Brazilian Symposium on Bioinformatics covers all aspects of bioinformatics and computational biology, including sequence analysis; motifs, and pattern matching; biological databases, data management, data integration, and data mining; biomedical text mining; structural, comparative, and functional genomics; personal genomics; protein structure, modeling, and simulation; gene identification, regulation and expression analysis; gene and protein interaction and networks; molecular docking; molecular evolution and phylogenetics; computational systems biology; computational proteomics; statistical analysis of molecular sequences; algorithms for problems in computational biology; applications in molecular biology, biochemistry, genetics, medicine, microbiology and associated subjects.
Identifying Transcription Factor Targets and Studying Human Complex Disease Genes
Transcription factors (TFs) have been characterized as mediators of human complex disease processes. The target genes of TFs also may be associated with disease. Identification of potential TF targets could further our understanding of gene-gene interactions underlying complex disease. We focused on two TFs, USF1 and ZNF217, because of their biological importance, especially their known genetic association with coronary artery disease (CAD), and the availability of chromatin immunoprecipitation microarray (ChIP-chip) results. First, we used USF1 ChIP-chip data as a training dataset to develop and evaluate several kernel logistic regression prediction models. Our most accurate predictor significantly outperformed standard PWM-based prediction methods. This novel prediction method enables a more accurate and efficient genome-scale identification of USF1 binding and associated target genes. Second, the results from independent linkage and gene expression studies suggest that ZNF217 also may be a candidate gene for CAD. We further investigated the role of ZNF217 for CAD in three independent CAD samples with different phenotypes. Our association studies of ZNF217 identified three SNPs having consistent association with CAD in three samples. Aorta expression profiling indicated that the proportion of the aorta with raised lesions was also positively correlated to ZNF217 expression. The combined evidence suggests that ZNF217 is a novel susceptibility gene for CAD. Finally, we applied our previously developed TF binding site (TFBS) prediction method to ZNF217. The performance of the prediction models of ZNF217 and USF1 are very similar. We demonstrated that our TFBS prediction method can be extended to other TFs. In summary, the results of this dissertation research are (1) evaluation of two TFs, USF1 and ZNF217, as susceptibility factors for CAD; (2) development of a generalized method for TFBS prediction; (3) prediction of TFBSs and target genes of two TFs, and identifica.
Compact Handbook of Computational Biology
The assimilation of computational methods into the life sciences has played an important role in advancing biological research. From sequencing genomes to discovering motifs in large collections of functionally equivalent sequences of nucleic acids and proteins, the value of powerful computational tools has become abundantly clear. The Compact Handbook of Computational Biology describes the foundational concepts, techniques, and challenges of biomolecular sequence analysis, biopolymer structure analysis and prediction, genomics, and molecular evolution. Comprising contributions from renowned scientists, many of whom pioneered current methodologies, the Compact Handbook of Computational Biology offers interdisciplinary and authoritative coverage of methods for analysis of nucleic acid and protein sequences and structures, definition and detection of motifs in nucleic acid and protein sequences, protein structure prediction, and discrete modeling of biopolymers. Specific computational topics include computer-assisted research on protein folding, computer-assisted studies of DNA-protein interactions, computer-assisted genomics, proteomics, and comparative genomics, and computer-assisted studies of genome evolution at the molecular (DNA) level. Offering a survey of specific algorithms that have proven successful in molecular biology, genomics, structural biology, and bioinformatics, this invaluable handbook is an authoritative source covering terminology, software, and applications of computational biology.
Protein Function Prediction for Omics Era
Gene function annotation has been a central question in molecular biology. The importance of computational function prediction is increasing because more and more large scale biological data, including genome sequences, protein structures, protein-protein interaction data, microarray expression data, and mass spectrometry data, are awaiting biological interpretation. Traditionally when a genome is sequenced, function annotation of genes is done by homology search methods, such as BLAST or FASTA. However, since these methods are developed before the genomics era, conventional use of them is not necessarily most suitable for analyzing a large scale data. Therefore we observe emerging development of computational gene function prediction methods, which are targeted to analyze large scale data, and also those which use such omics data as additional source of function prediction. In this book, we overview this emerging exciting field. The authors have been selected from 1) those who develop novel purely computational methods 2) those who develop function prediction methods which use omics data 3) those who maintain and update data base of function annotation of particular model organisms (E. coli), which are frequently referred
Modern Genome Annotation
An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome.
The genomic revolution that has spawned microarrays and high throughput technologies has produced vast amounts of complex biological data that require integration and multidimensional analysis. Bioinformatics incorporates sub-disciplines ranging from databases and ontologies to the modelling of complex biological systems by way of molecular evolution and protein structure prediction. This new book provides state-of-the-art research from around the world.
Issues in Biological and Life Sciences Research 2011 Edition
Issues in Biological and Life Sciences Research: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Biological and Life Sciences Research. The editors have built Issues in Biological and Life Sciences Research: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Biological and Life Sciences Research in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Biological and Life Sciences Research: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.