Automated Gene Function Prediction

Automated Gene Function Prediction
Author: Vinayagam Arunachalam
Publisher:
Total Pages: 112
Release: 2007
Genre: Health & Fitness
ISBN: 9783836421577

Download Automated Gene Function Prediction Book in PDF, Epub and Kindle

The objective of biological research is to understand the structural and the functional aspects of life. Though living organisms are diverse in almost every aspect, they are made of cells, and share the same machinery for their basic functions. The structural and functional aspect of life is traceable to genes, given that the information from the genes determine the protein composition and thereby the function of the cell. Hence, predicting the functions of individual genes is the gate way for understanding the blueprint of life. The rationale behind the ongoing genome sequencing projects is to utilize the sequence information to understand the genes and their functions. The exponential increase in the amount of sequence information enunciated the need for an automated approach to acquire knowledge about their biological function. This book introduces the general strategies used in the automated annotation of genes and protein sequences. Specifically, it describes a method utilizing the machine learning approach to predict gene function. This book is addressed to researchers involved in predicting gene function and applying machine learning algorithms to other biological problems.

The Gene Ontology Handbook

The Gene Ontology Handbook
Author: Christophe Dessimoz
Publisher:
Total Pages: 298
Release: 2020-10-08
Genre: Science
ISBN: 9781013267710

Download The Gene Ontology Handbook Book in PDF, Epub and Kindle

This book provides a practical and self-contained overview of the Gene Ontology (GO), the leading project to organize biological knowledge on genes and their products across genomic resources. Written for biologists and bioinformaticians, it covers the state-of-the-art of how GO annotations are made, how they are evaluated, and what sort of analyses can and cannot be done with the GO. In the spirit of the Methods in Molecular Biology book series, there is an emphasis throughout the chapters on providing practical guidance and troubleshooting advice. Authoritative and accessible, The Gene Ontology Handbook serves non-experts as well as seasoned GO users as a thorough guide to this powerful knowledge system. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Gene Prediction

Gene Prediction
Author: Martin Kollmar
Publisher: Humana Press
Total Pages: 284
Release: 2019-05-19
Genre: Science
ISBN: 9781493991723

Download Gene Prediction Book in PDF, Epub and Kindle

This volume introduces software used for gene prediction with focus on eukaryotic genomes. The chapters in this book describe software and web server usage as applied in common use-cases, and explain ways to simplify re-annotation of long available genome assemblies. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary computational requirements, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Gene Prediction: Methods and Protocols is a valuable resource for researchers and research groups working on the assembly and annotation of single species or small groups of species. Chapter 3 is available open access under a CC BY 4.0 license via link.springer.com.

A Gene Ontology Based Computational Approach for the Prediction of Protein Functions

A Gene Ontology Based Computational Approach for the Prediction of Protein Functions
Author: Saket Kharsikar
Publisher:
Total Pages: 92
Release: 2007
Genre: Biomedical engineering
ISBN:

Download A Gene Ontology Based Computational Approach for the Prediction of Protein Functions Book in PDF, Epub and Kindle

Numerous genome projects have produced a large and ever increasing amount of genomic sequence data. However, the biological functions of many proteins encoded by the sequences remain unknown. Protein function annotation and prediction become an essential and challenging task of post-genomic research. In this research, we present an automated protein function prediction system based on a set of proteins of known biological functions. The functions of the proteins are characterized with Gene Ontology (GO) annotations. The prediction system uses a novel measure to calculate the pair-wise overall similarity between protein sequences. The protein function prediction is performed based on the GO annotations of similar sequences using a weighted k-nearest neighbor method. We show the prediction accuracies obtained using the model organism yeast (Sacchyromyces cerevisiae). The results indicate that the weighted k-nearest neighbor method significantly outperforms the regular k-nearest neighbor method for protein biological function prediction.

Sequence — Evolution — Function

Sequence — Evolution — Function
Author: Eugene V. Koonin
Publisher: Springer Science & Business Media
Total Pages: 482
Release: 2013-06-29
Genre: Science
ISBN: 1475737831

Download Sequence — Evolution — Function Book in PDF, Epub and Kindle

Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.

Human Gene Mutation

Human Gene Mutation
Author: David N. Cooper
Publisher: Taylor & Francis
Total Pages: 412
Release: 1995
Genre: Science
ISBN: 9781859960554

Download Human Gene Mutation Book in PDF, Epub and Kindle

Within the last decade, much progress has been made in the analysis and diagnosis of human inherited disease, and in the characterization of the underlying genes and their associated pathological lesions.

Protein Function Prediction Using Decision Tree Technique

Protein Function Prediction Using Decision Tree Technique
Author: Venkata Rama Kumar Swamy Yedida
Publisher:
Total Pages: 80
Release: 2008
Genre: Computational biology
ISBN:

Download Protein Function Prediction Using Decision Tree Technique Book in PDF, Epub and Kindle

The human genome project and numerous other genome projects have produced a large and ever increasing amount of sequence data. One of the main research challenges in the post-genomic era is to understand the relationship between the nucleotide sequences of genes and the functions of the proteins they encode. The objective of this thesis is to develop an automated protein function prediction system that is based on a set of homologous proteins and gene ontology categories. A novel measure based on a set of best local alignments is used to identify the homologues. The biological functions of the homologous proteins are characterized with gene ontology annotations. The protein function prediction is performed based on data mining models using decision trees. The models are trained and tested using the complete proteome of model organism yeast. The results show that the prediction accuracy depends on individual functional groups of proteins. There is a general trend of decreased model accuracy with the level of a group on the gene ontology graph, but the accuracy at a fix level varies from group to group. The prediction accuracy varies from group to group, no obvious accuracy changes from one level to another. These variations of accuracy illustrate certain limitations of sequence-based protein function prediction methods. But the fundamental assumption used in this thesis, similar amino acid sequences implying similar biological functions, is largely valid. The prediction results based on the proteome of yeast indicate that the accuracies for most of the functional groups are over 75%. We conclude that the decision tree model can be used as a preliminary tool for protein function prediction although the prediction results need to be verified through other means.

Prediction of Protein Structures, Functions, and Interactions

Prediction of Protein Structures, Functions, and Interactions
Author: Janusz M. Bujnicki
Publisher: John Wiley & Sons
Total Pages: 302
Release: 2008-12-23
Genre: Science
ISBN: 9780470741900

Download Prediction of Protein Structures, Functions, and Interactions Book in PDF, Epub and Kindle

The growing flood of new experimental data generated by genome sequencing has provided an impetus for the development of automated methods for predicting the functions of proteins that have been deduced by sequence analysis and lack experimental characterization. Prediction of Protein Structures, Functions and Interactions presents a comprehensive overview of methods for prediction of protein structure or function, with the emphasis on their availability and possibilities for their combined use. Methods of modeling of individual proteins, prediction of their interactions, and docking of complexes are put in the context of predicting gene ontology (biological process, molecular function, and cellular component) and discussed in the light of their contribution to the emerging field of systems biology. Topics covered include: first steps of protein sequence analysis and structure prediction automated prediction of protein function from sequence template-based prediction of three-dimensional protein structures: fold-recognition and comparative modelling template-free prediction of three-dimensional protein structures quality assessment of protein models prediction of molecular interactions: from small ligands to large protein complexes macromolecular docking integrating prediction of structure, function, and interactions Prediction of Protein Structures, Functions and Interactions focuses on the methods that have performed well in CASPs, and which are constantly developed and maintained, and are freely available to academic researchers either as web servers or programs for local installation. It is an essential guide to the newest, best methods for prediction of protein structure and functions, for researchers and advanced students working in structural bioinformatics, protein chemistry, structural biology and drug discovery.