methods for computational gene prediction

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Methods For Computational Gene Prediction

Author : William H. Majoros
ISBN : 0521877512
Genre : Computers
File Size : 72. 64 MB
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A self-contained, rigorous text describing models used to identify genes in genomic DNA sequences.

Advances In Bioinformatics And Computational Biology

Author : Osmar Norberto de Souza
ISBN : 9783642228247
Genre : Computers
File Size : 32. 29 MB
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This book constitutes the proceedings of the 6th Brazilian Symposium on Bioinformatics, BSB 2011, held in Brasília, Brazil, in August 2011. The 8 full papers and 4 extended abstracts presented were carefully peer-reviewed and selected for inclusion in this book. The BSB topics of interest cover many areas of bioinformatics that range from theoretical aspects of problems in bioinformatics to applications in molecular biology, biochemistry, genetics, and associated subjects.

Fast And Accurate Gene Prediction By Protein Homology

Author : Rong She
ISBN : OCLC:930766234
Genre : Gene mapping
File Size : 75. 84 MB
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The fast development of genome sequencing technologies has provided scientists with enormous amount of DNA sequences that keep increasing exponentially. The task of analyzing these DNA sequences and deducing useful knowledge from them remains challenging. One of the most important steps towards the understanding of genomes is gene prediction, which is determining the positions of genes and their components (including exons and introns) on the DNA sequence. There have been many attempts on computational gene prediction. The two main categories of gene prediction methods are Ab initio methods and homology-based methods. The Ab initio methods are usually sensitive in finding genes in novel genomes but often produce many false positives. The homology-based methods, on the other hand, usually have higher specificity, but are limited to finding genes that have homologous partners. With the accumulation of genome sequences of related species, there has been a growing demand for better and faster homology-based gene prediction programs. In this thesis, I present a homology-based gene prediction framework that utilizes protein homology in determining positions of protein-coding genes. A protein sequence (the product of gene) is used as a query to help in finding genes that are homologous to the query protein. The framework consists of two major components. First, local alignments between the query protein and the genome are assembled into gene regions where potential homologous genes are located. Next, each potential gene region is examined for gene signals and gene models are resolved by utilizing the alignment information provided by the local alignments. The experiments on genomes of two closely related species Caenorhabditis elegans and Caenorhabditis briggsae demonstrated that this method is both accurate and efficient. In particular, it runs hundreds of times faster than GeneWise, a popular homology-based gene prediction program, while being competitive in accuracy. Experiments have also been done on the human genome with a much larger size than C. elegans and C. briggsae, which showed similar performance behaviours of genBlast.

Computational Methods In Biomedical Research

Author : Ravindra Khattree
ISBN : 1420010921
Genre : Mathematics
File Size : 81. 45 MB
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Continuing advances in biomedical research and statistical methods call for a constant stream of updated, cohesive accounts of new developments so that the methodologies can be properly implemented in the biomedical field. Responding to this need, Computational Methods in Biomedical Research explores important current and emerging computational statistical methods that are used in biomedical research. Written by active researchers in the field, this authoritative collection covers a wide range of topics. It introduces each topic at a basic level, before moving on to more advanced discussions of applications. The book begins with microarray data analysis, machine learning techniques, and mass spectrometry-based protein profiling. It then uses state space models to predict US cancer mortality rates and provides an overview of the application of multistate models in analyzing multiple failure times. The book also describes various Bayesian techniques, the sequential monitoring of randomization tests, mixed-effects models, and the classification rules for repeated measures data. The volume concludes with estimation methods for analyzing longitudinal data. Supplying the knowledge necessary to perform sophisticated statistical analyses, this reference is a must-have for anyone involved in advanced biomedical and pharmaceutical research. It will help in the quest to identify potential new drugs for the treatment of a variety of diseases.

Introduction To Computational Biology

Author : Bernhard Haubold
ISBN : 9783764373870
Genre : Science
File Size : 90. 5 MB
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Written with the advanced undergraduate in mind, this book introduces into the field of Bioinformatics. The authors explain the computational and conceptional background to the analysis of large-scale sequence data. Many of the corresponding analysis methods are rooted in evolutionary thinking, which serves as a common thread throughout the book. The focus is on methods of comparative genomics and subjects covered include: alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs). The volume contains exercises, questions & answers to selected problems.

Genomics And Proteomics

Author : Sándor Suhai
ISBN : 9780306468230
Genre : Science
File Size : 49. 94 MB
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Genome research will certainly be one of the most important and exciting sci- tific disciplines of the 21st century. Deciphering the structure of the human genome, as well as that of several model organisms, is the key to our understanding how genes fu- tion in health and disease. With the combined development of innovativetools, resources, scientific know-how, and an overall functional genomic strategy, the origins of human and other organisms’geneticdiseases can be traced. Scientificresearch groups and dev- opmental departments of several major pharmaceutical and biotechnological companies are using new, innovative strategies to unravel how genes function, elucidating the gene protein product, understanding how genes interact with others-both in health and in the disease state. Presently, the impact of the applications of genome research on our society in medicine, agriculture and nutrition will be comparable only to that of communication technologies. In fact, computational methods, including networking, have been playing a substantial role even in genomics and proteomics from the beginning. We can observe, however, a fundamental change of the paradigm in life sciences these days: research focused until now mostly on the study of single processes related to a few genes or gene products, but due to technical developments of the last years we can now potentially identify and analyze all genes and gene products of an organism and clarify their role in the network of lifeprocesses.

Microbial Functional Genomics

Author : Jizhong Zhou
ISBN : 0471071900
Genre : Medical
File Size : 89. 70 MB
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Genomics: toward a genome-level understanding of the structure, functions, and evolution of bioloical systems; Microbial diversity and genomics. Computational genome annotation. Microbial evolution from a genomics perspective. Computational methods for functional prediction of genes. DNA microarray technology. Microarray gene expression data analysis. Mutagenesis as a genomic tool for studying gene function. Mass spectrometry. Identification of protein-ligand interactions. The functional genomics of model organisms: addressing old questions from a new perspective. Functional genomic analysis of bacterial pathogens and environmentally significant microorganisms. The impact of genomics on antimicrobial drug discovery and toxicology. Application of microarray-based genomic technology to mutation analysis and microbial detection. Future perspectives: genomics beyond single cells.

Handbook Of Research On Computational Intelligence Applications In Bioinformatics

Author : Dash, Sujata
ISBN : 9781522504283
Genre : Computers
File Size : 24. 57 MB
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Developments in the areas of biology and bioinformatics are continuously evolving and creating a plethora of data that needs to be analyzed and decrypted. Since it can be difficult to decipher the multitudes of data within these areas, new computational techniques and tools are being employed to assist researchers in their findings. The Handbook of Research on Computational Intelligence Applications in Bioinformatics examines emergent research in handling real-world problems through the application of various computation technologies and techniques. Featuring theoretical concepts and best practices in the areas of computational intelligence, artificial intelligence, big data, and bio-inspired computing, this publication is a critical reference source for graduate students, professionals, academics, and researchers.

Knowledge Discovery And Emergent Complexity In Bioinformatics

Author : Karl Tuyls
ISBN : 9783540710363
Genre : Science
File Size : 28. 48 MB
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This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Knowledge Discovery and Emergent Complexity in Bioinformatics, KDECB 2006, held in Ghent, Belgium, in May 2006, in connection with the 15th Belgium-Netherlands Conference on Machine Learning. The 12 revised full papers cover various topics in the areas of knowledge discovery and emergent complexity research in bioinformatics.

Computational Methods For Understanding Bacterial And Archaeal Genomes

Author : Ying Xu
ISBN : 9781860949838
Genre : Bacterial genomes
File Size : 25. 15 MB
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Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative view of bacterial and archaeal genomes, and how information is encoded differently in them, is also presented. Combining theoretical discussions and computational techniques, the book serves as a valuable introductory textbook for graduate-level microbial genomics and informatics courses.

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