Bioinformatics

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Bioinformatics: краткое содержание, описание и аннотация

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Praise for the third edition of
“This book is a gem to read and use in practice.”
— "This volume has a distinctive, special value as it offers an unrivalled level of details and unique expert insights from the leading computational biologists, including the very creators of popular bioinformatics tools."
— “A valuable survey of this fascinating field. . . I found it to be the most useful book on bioinformatics that I have seen and recommend it very highly.”
— “This should be on the bookshelf of every molecular biologist.”
— The field of bioinformatics is advancing at a remarkable rate. With the development of new analytical techniques that make use of the latest advances in machine learning and data science, today’s biologists are gaining fantastic new insights into the natural world’s most complex systems. These rapidly progressing innovations can, however, be difficult to keep pace with.
The expanded fourth edition of the best-selling
aims to remedy this by providing students and professionals alike with a comprehensive survey of the current field. Revised to reflect recent advances in computational biology, it offers practical instruction on the gathering, analysis, and interpretation of data, as well as explanations of the most powerful algorithms presently used for biological discovery.
offers the most readable, up-to-date, and thorough introduction to the field for biologists at all levels, covering both key concepts that have stood the test of time and the new and important developments driving this fast-moving discipline forwards.
This new edition features: 
New chapters on metabolomics, population genetics, metagenomics and microbial community analysis, and translational bioinformatics A thorough treatment of statistical methods as applied to biological data Special topic boxes and appendices highlighting experimental strategies and advanced concepts Annotated reference lists, comprehensive lists of relevant web resources, and an extensive glossary of commonly used terms in bioinformatics, genomics, and proteomics
is an indispensable companion for researchers, instructors, and students of all levels in molecular biology and computational biology, as well as investigators involved in genomics, clinical research, proteomics, and related fields.

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2 Chapter 2 Figure 2.1 The exponential growth of GenBank in terms of number of nucleotides... Figure 2.2 Results of a text-based Entrez query against PubMed using Boolean o... Figure 2.3 An example of a PubMed record in Abstract format, as returned throu... Figure 2.4 Neighbors to an entry found in PubMed. The original entry from Figu... Figure 2.5 The Entrez Gene page for the DCC (deleted in colorectal carcinoma) ... Figure 2.6 A section of the Database of Single Nucleotide Polymorphisms (dbSNP... Figure 2.7 Entries in the RefSeq protein database corresponding to the origina... Figure 2.8 The RefSeq entry for the netrin receptor, the protein product of th... Figure 2.9 The same RefSeq entry for the netrin receptor shown in Figure 2.8, ... Figure 2.10 Protein structures associated with the RefSeq entry for the human ... Figure 2.11 The structure summary page for pdb:4URT, the crystal structure of ... Figure 2.12 A list of structures deemed similar to pdb:4URT using VAST+. The t... Figure 2.13 Online Mendelian Inheritance in Man (OMIM) entries related to the Figure 2.14 The Online Mendelian Inheritance in Man (OMIM) entry for the DCC g... Figure 2.15 An example of a list of allelic variants that can be found through... Figure 2.16 The ClinicalTrials.gov page showing all actively recruiting clinic... Figure 2.17 A clickable map showing where actively recruiting clinical trials ... Figure 2.18 The Mouse Genome Informatics (MGI) entry for the Dcc gene in mouse... Figure 2.19 The Zebrafish Information Network (ZFIN) gene page for the dcc gen... Figure 2.20 An example of gene expression data available through the Zebrafish...

3 Chapter 3 Figure 3.1 The BLOSUM62 scoring matrix (Henikoff and Henikoff 1992). BLOSUM62 ... Figure 3.2 A nucleotide scoring table. The scoring for the four nucleotide bas... Figure 3.3 The initiation of a BLAST search. The search begins with query word... Figure 3.4 BLAST search extension. Length of extension represents the number o... Figure 3.5 The National Center for Biotechnology Information (NCBI) BLAST land... Figure 3.6 The upper portion of the BLASTP query page. The first section in th... Figure 3.7 The lower portion of the BLASTP query page, showing algorithm param... Figure 3.8 Graphical display of BLASTP results. The query sequence is represen... Figure 3.9 The BLASTP “hit list.” For each sequence found, the user is present... Figure 3.10 Detailed information on a representative BLASTP hit. The header pr... Figure 3.11 Performing a BLAST 2 Sequences alignment. Clicking the check box a... Figure 3.12 Typical output from a BLAST 2 Sequences alignment, based on the qu... Figure 3.13 Constructing a position-specific scoring matrix (PSSM). In the upp... Figure 3.14 Performing a PSI-BLAST search. See text for details. Figure 3.15 Selecting algorithm parameters for a PSI-BLAST search. See text fo... Figure 3.16 Results of the first round of a PSI-BLAST search. For each sequenc... Figure 3.17 Results of the second round of a PSI-BLAST search. New sequences i... Figure 3.18 Submitting a BLAT query. A rat clone from the Cancer Genome Anatom... Figure 3.19 Results of a BLAT query. Based on the query submitted in Figure 3.... Figure 3.20 The FASTA search strategy. (a) Once FASTA determines words of leng... Figure 3.21 Search summary from a protein–protein FASTA search, using the sequ... Figure 3.22 Hit list for the protein–protein FASTA search described in Figure ...

4 Chapter 4 Figure 4.1 The home page of the UCSC Genome Browser, showing a query for the g... Figure 4.2 The default view of the UCSC Genome Browser, showing the genomic co... Figure 4.3 The genomic context of the human HIF1A gene, after clicking on zoom ... Figure 4.4 The RefSeq Track Settings page. The track settings pages are used t... Figure 4.5 The genomic context of the human HIF1A gene, after displaying RefSe... Figure 4.6 The Get Genomic Sequence page that provides an interface for users ... Figure 4.7 The genomic context of the human HIF1A gene, after changing the dis... Figure 4.8 Configuring the track settings for the Common SNPs(150) track. Set ... Figure 4.9 The genomic context of the human HIF1A gene, after changing the col... Figure 4.10 The GTEx Gene track, which depicts median gene expression levels i... Figure 4.11 BLAT search at the UCSC Genome Browser. (a) This page shows the re... Figure 4.12 Configuring the UCSC Table Browser. The link to the Table Browser ... Figure 4.13 The home page of the Ensembl Genome Browser, showing a query for t... Figure 4.14 The Gene tab for the human PAH gene. This landing page provides li... Figure 4.15 Computationally predicted orthologs of the human PAH gene, from th... Figure 4.16 The Location tab for the human PAH gene. The Location tab is divid... Figure 4.17 Zooming in on the bottom section of the Location tab from Figure 4... Figure 4.18 The Ensembl Variant tab. (a) To get more details about SNP rs76296... Figure 4.19 The Ensembl Regulatory Build track. (a) Go to Configure this page ... Figure 4.20 The Synteny view at Ensembl. (a) An overview of the syntenic block... Figure 4.21 Ensembl BLAST output, showing an alignment between the human ADAM1... Figure 4.22 Using BioMart to retrieve the mouse orthologs of the human RefSeqs... Figure 4.23 JBrowse display of a predicted Mnemiopsis gene ( ML05372a ) from the...

5 Chapter 5 Figure 5.1 A simplified depiction of a prokaryotic gene or open reading frame ... Figure 5.2 A simplified depiction of a eukaryotic gene illustrating the multi-... Figure 5.3 A schematic illustration of the upstream regions of a eukaryotic ge... Figure 5.4 A schematic illustration of the splice site regions around exons an... Figure 5.5 Sample output from a GENSCAN analysis of the uroporphyrinogen decar... Figure 5.6 Schematic representation of measures of gene prediction accuracy at...Figure 5.7 The typical L-shaped structure of a tRNA molecule. This depicts the...Figure 5.8 A screenshot montage of the PHASTER web server showing the website ...Figure 5.9 A screenshot of a BASys bacterial genome annotation output for the ...

6 Chapter 6Figure 6.1 The three levels of organization of RNA structure. (a) The primary ...Figure 6.2 The RNA secondary structure of the 3′ untranslated region of the Dr ...Figure 6.3 An illustration of the equilibria of RNA structures in solution. (a...Figure 6.4 Prediction of conformational free energy for a conformation of RNA ...Figure 6.5 A simple RNA pseudoknot. This figure illustrates two representation...Figure 6.6 The input form for the version 3.1 Mfold server. (a) The top and (b...Figure 6.7 The output page for the Mfold server. Please refer to the text for ...Figure 6.8 Sample output from the Mfold web server, version 3.1. (a) The secon...Figure 6.9 RNAstructure web server input form. (a) The top and (b) the bottom ...Figure 6.10 Sample output from the RNAstructure web server showing the predict...Figure 6.11 Input form for the RNAstructure web server for multiple-sequence p...Figure 6.12 Sample output from the RNAstructure web server for multiple-sequen...

7 Chapter 7Figure 7.1 Dashboard of the PredictProtein web server. PredictProtein (Yachdav...Figure 7.2 Protein secondary structure. Experimentally determined three-dimens...Figure 7.3 Accessible surface area (ASA). The ASA describes the surface that i...Figure 7.4 Protein secondary structure. Prediction of secondary structure, sol...Figure 7.5 Types of transmembrane proteins. Experimentally determined three-di...Figure 7.6 Transmembrane helix prediction by TMSEG. TMSEG (Bernhofer et al. 20...Figure 7.7 Annotations of human tumor suppressor P53 (P53_HUMAN). (a) InterPro...Figure 7.8 Prediction of subcellular localization. Visual output from LocTree3...Figure 7.9 From predicting single amino acid sequence variant (SAV) effects to...

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