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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/4100?offset=50</link>
	<atom:link href="https://bioinformaticsonline.com/related/4100?offset=50" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</guid>
	<pubDate>Tue, 22 Jan 2019 06:26:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</link>
	<title><![CDATA[Katuali is a flexible consensus pipeline implemented in Snakemake to basecall, assemble, and polish Oxford Nanopore Technologies&#039; sequencing data]]></title>
	<description><![CDATA[<ul>
<li>Run a pipeline processing fast5s to a consensus in a single command.</li>
<li>Recommended fixed "standard" and "fast" pipelines.</li>
<li>Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath.</li>
<li>Seemless distribution of tasks over local or distributed compute.</li>
<li>Highly configurable.</li>
<li>Open source (Mozilla Public License 2.0).</li>
</ul>
<p>Documentation can be found at&nbsp;<a href="https://nanoporetech.github.io/katuali/">https://nanoporetech.github.io/katuali/</a>.</p><p>Address of the bookmark: <a href="https://github.com/nanoporetech/katuali" rel="nofollow">https://github.com/nanoporetech/katuali</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/39827/prof-dr-med-andreas-ramming</guid>
  <pubDate>Wed, 07 Aug 2019 03:25:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Prof. Dr. med. Andreas Ramming]]></title>
  <description><![CDATA[
<p>In many autoimmune diseases, a misdirected immune response leads to chronic inflammation and subsequently to fibrotic and degenerative tissue remodeling. Therapeutic options are available for inflammatory joint diseases, but only about 40% of patients respond to these existing therapies on a permanent basis. In the remaining cases, these therapies miss their target from the beginning or later during the course of treatment failure. There are currently no causal therapies available for the treatment of fibrotic autoimmune diseases such as systemic sclerosis. Therefore, there is an urgent need to develop new therapeutic options for the treatment of fibrotic and synovitic autoimmune diseases. His group is therefore deal with the molecular mechanisms of these misdirected signaling pathways for the development of novel, targeted therapies</p>

<p>http://www.medizin3.uk-erlangen.de/forschung/arbeitsgruppen/matrixbiologie-entzuendliche-signalwege-in-arthritis-und-fibrose/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41046/iseqqc-a-tool-for-expression-based-quality-control-in-rna-sequencing</guid>
	<pubDate>Sun, 16 Feb 2020 08:47:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41046/iseqqc-a-tool-for-expression-based-quality-control-in-rna-sequencing</link>
	<title><![CDATA[iSeqQC: a tool for expression-based quality control in RNA sequencing]]></title>
	<description><![CDATA[<p><span>iSeqQC, an expression-based QC tool that detects outliers either produced due to variable laboratory conditions or due to dissimilarity within a phenotypic group. iSeqQC implements various statistical approaches including unsupervised clustering, agglomerative hierarchical clustering and correlation coefficients to provide insight into outliers.</span></p>
<p><a href="http://cancerwebpa.jefferson.edu/iSeqQC/">http://cancerwebpa.jefferson.edu/iSeqQC/</a></p>
<p><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8</a></p><p>Address of the bookmark: <a href="https://github.com/gkumar09/iSeqQC" rel="nofollow">https://github.com/gkumar09/iSeqQC</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42485/fastprongs-fast-preprocessing-of-next-generation-sequencing-reads</guid>
	<pubDate>Sat, 26 Dec 2020 08:35:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42485/fastprongs-fast-preprocessing-of-next-generation-sequencing-reads</link>
	<title><![CDATA[FastProNGS: fast preprocessing of next-generation sequencing reads]]></title>
	<description><![CDATA[<p><span>FastProNGS to integrate the quality control process with automatic adapter removal. Parallel processing was implemented to speed up the process by allocating multiple threads. Compared with similar up-to-date preprocessing tools, FastProNGS is by far the fastest.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/Megagenomics/FastProNGS" rel="nofollow">https://github.com/Megagenomics/FastProNGS</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data</guid>
	<pubDate>Fri, 04 Oct 2024 02:45:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data</link>
	<title><![CDATA[Libraries or management tools for high throughput sequencing data]]></title>
	<description><![CDATA[<ul>
<li><a href="http://gatb.inria.fr/"><span>GATB</span></a>&nbsp;Library.&nbsp;The&nbsp;<span>Genome Analysis Toolbox with de-Bruijn graph.&nbsp;</span>A large part of tools developed by the GenScale team are based on this library.<br />These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (<em>e.g.</em>&nbsp;metagenomes). Among them are (the full is available here:&nbsp;<a href="https://gatb.inria.fr/software/">https://gatb.inria.fr/software/</a>):</li>
<li><a href="https://github.com/morispi/LRez"><span>LRez</span></a>: C++ Library and toolkit for the barcode-based management and indexation of linked-read datasets.</li>
</ul><h2>Variant calling and/or genotyping</h2><ul>
<li><a href="https://gatb.inria.fr/software/discosnp/" title="DiscoSNP">DiscoSNP++ and&nbsp;discoSnpRAD</a>: Reference-free small variant discovery (SNPs and indels)</li>
<li><a href="https://gatb.inria.fr/software/mind-the-gap/" title="MindTheGap">MindTheGap</a>: Detection and assembly of large insertion variants</li>
<li><a href="https://gatb.inria.fr/software/takeabreak/" title="TakeABreak">TakeABreak</a>:&nbsp;reference-free inversion discovery tool</li>
<li><a href="https://github.com/llecompte/SVJedi">SVJedi</a>: Structural Variant genotyper with long read data</li>
<li><a href="https://github.com/SandraLouise/SVJedi-graph">SVJedi-graph</a>: Structural Variant genotyper with long read data using a variation graph</li>
</ul><h2>Sequence assembly</h2><ul>
<li><a href="https://github.com/cguyomar/MinYS">MinYS</a>: reference-guided genome assembly in metagenomics data</li>
<li><a href="https://github.com/anne-gcd/MTG-Link">MTG-link</a>: local assembly tool for linked-read data</li>
<li><a href="https://gatb.inria.fr/software/minia/" title="Minia">Minia</a>: De novo short read assembler</li>
<li><a href="https://gatb.inria.fr/de-novo-genome-assembly/">de-novo pipeline</a>:&nbsp;<em>de-novo</em>&nbsp;assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes</li>
<li><a href="https://gatb.inria.fr/software/mapsembler/" title="Mapsembler2">Mapsembler2</a>: Targeted assembly (not maintained)</li>
</ul><h2>Managing k-mers &amp; indexation</h2><ul>
<li><a href="https://github.com/lrobidou/findere">findere</a>:&nbsp;simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
<ul>
<li><a href="https://github.com/lrobidou/fimpera">fimpera</a>&nbsp;extends findere adding the abundance information.</li>
</ul>
</li>
<li><a href="https://github.com/tlemane/kmtricks">kmtricks</a>:&nbsp;modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.</li>
<li><a href="https://github.com/tlemane/kmindex">kmindex&nbsp;</a>is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.</li>
<li><a href="https://github.com/pierrepeterlongo/back_to_sequences">back to sequences</a>: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.</li>
<li><a href="https://github.com/vicLeva/bqf">Backpack Quotient Filter</a>:&nbsp;k-mer indexing data structure with abundance</li>
<li><a href="http://github.com/GATB/rconnector">short read connector</a>:&nbsp;Detect similar reads from potentially large read set</li>
<li><a href="https://gatb.inria.fr/software/dsk/" title="DSK">DSK</a>:&nbsp;Count K-mer in sequences</li>
</ul><h2>Pangenome graph manipulation</h2><ul>
<li><a href="https://github.com/Tharos-ux/pancat">Pancat</a>: Pangenome Comparison and Analysis Toolkit</li>
<li><a href="https://pypi.org/project/gfagraphs/">GFAGraphs</a>: a Python library to handle pangenome graph files in GFA format.</li>
</ul><h2>Comparative metagenomics with k-mers</h2><ul>
<li><a href="https://github.com/GATB/simka">Simka and SimkaMin</a>:&nbsp;Comparative metagenomics for large-scale datasets</li>
<li><a href="https://team.inria.fr/genscale/high-throughput-sequence-analysis/compreads-metagenomic-data-analysis/">Comparead &amp; Commet</a>:&nbsp;comparison of metagenomic datasets</li>
</ul><h2>Species and bacterial strains identification</h2><ul>
<li><a href="https://github.com/gsiekaniec/ORI">ORI</a>: software using long nanopore reads to identify bacteria present in a sample at the strain level</li>
<li><a href="https://github.com/kevsilva/StrainFLAIR">StrainFLAIR</a>:&nbsp;STRAIN-level proFiLing using vArIation gRaph</li>
</ul><h2>General-purpose sequencing data manipulation</h2><ul>
<li><a href="https://team.inria.fr/genscale/ngs-software/gassst/">GASSST</a>:&nbsp;long read mapper</li>
<li><a href="https://gatb.inria.fr/software/leon/" title="Leon">Leon</a>: short read compressor (now included in GATB-core)</li>
<li><a href="https://gatb.inria.fr/software/bloocoo/" title="Bloocoo">Bloocoo</a>:&nbsp;short read corrector</li>
<li><a href="https://github.com/GATB/bcalm">BCALM</a>:&nbsp;Construct compacted de Bruijn graphs (unitigs)</li>
</ul><h2>&nbsp;Protein Structure</h2><ul>
<li><a href="https://team.inria.fr/genscale/protein-structure/a-purva-contact-map-overlap-solver/">A_Purva</a>:&nbsp;Contact Map Overlap solver</li>
<li><a href="https://team.inria.fr/genscale/protein-structure/md-jeep-distance-geomtry-solver/">MD-Jeep</a>:&nbsp;Distance Geometry solver</li>
<li><a href="https://team.inria.fr/genscale/csa-comparative-structural-alignment/">CSA</a>:&nbsp;Comparative Structural Alignment</li>
</ul><h2>Workflow</h2><ul>
<li><a href="https://team.inria.fr/genscale/workflows/slicee/">SLICEE</a>:&nbsp;parallel execution of bioinformatics workflows</li>
</ul><h3>Comparative Genomics</h3><ul>
<li><a href="https://team.inria.fr/genscale/comparative-genomics/cassis/">CASSIS</a>:&nbsp;detection of rearrangement breakpoints</li>
<li><a href="https://team.inria.fr/genscale/high-throughput-sequence-analysis/plast-intensive-sequence-comparison/">PLAST</a>:&nbsp;intensive bank-to-bank sequence comparison</li>
<li><a href="https://github.com/stephanierobin/DrjBreakpointFinder">DRJBreakpointFinder</a>: detection and precise localization of excision sites in proviral segments</li>
</ul>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/41804/useful-links-to-therapy-disease-drug-and-drug-target-network-data</guid>
	<pubDate>Mon, 01 Jun 2020 11:47:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/41804/useful-links-to-therapy-disease-drug-and-drug-target-network-data</link>
	<title><![CDATA[Useful links to therapy, disease, drug and drug-target network data:]]></title>
	<description><![CDATA[<p>Useful links to therapy, disease, drug and drug-target network data:</p><p><strong>DrugBank:</strong></p><p>a bioinformatics- cheminformatics resource combining detailed drug data with comprehensive drug target information with &gt;4900 drug (~3500 experimental) and &gt;1500 non-redundant protein entries http://www.drugbank.ca/</p><p><strong>Drug-Target Network:</strong></p><p>network data of 890 drugs and 394 target human proteins http://www.nature.com/nbt/journal/v25/ n10/suppinfo/nbt1338_S1.html</p><p><strong>Drug-Therapy Network:</strong></p><p>three layers of drug-therapy networks according to the ATC classification http://www.biomedcentral.com/1471-2210/8/5/additional/</p><p><strong>FDA Orange Book:</strong></p><p>approved drug products with therapeutic equivalence evaluations http://www.fda.gov/cder/ob/HIDdb: Thomson Investigational drugs database including information on 107000 patents, 25000 investigational drugs and 80000 chemical structures http://scientific.thomson.com/products/iddb/HOMIM: a knowledgebase of human genes and genetic disorders http://www.ncbi.nlm.nih.gov/ sites/entrez?db=omim</p><p><strong>PDTD:</strong></p><p>3D drug target structure database with a target identification option http://www.dddc.ac.cn/pdtd/</p><p><strong>Predicted drug targets:</strong></p><p>a set of 1383 predicted drug targets http://www.biomedcentral.com/1471-2105/8/353/additional/ [25] Protein ligand network: a network of 4208 ligands and ~15000 binding sites http://pbil.kaist.ac.kr/~parkkw/Lnet/</p><p><strong>TDR Targets Database:</strong></p><p>identification and ranking targets against neglected tropical diseases http://tdrtargets.org/</p><p><strong>Therapeutic Target Database:</strong></p><p>lists &gt;1500 therapeutic targets, disease conditions and corresponding drugs http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/11603/ncbi-webinar</guid>
	<pubDate>Sun, 08 Jun 2014 02:47:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11603/ncbi-webinar</link>
	<title><![CDATA[NCBI Webinar]]></title>
	<description><![CDATA[<p>In less than two weeks, NCBI will offer a webinar entitled "Introducing 3 NCBI Resources to Navigate Testing for Disease Linked Variants: MedGen, GTR and ClinVar". This webinar will delve into the lifecycle of genetic testing and teach attendees how to navigate the NIH Genetic Testing Registry, ClinVar, and MedGen resources. These resources can be used to prepare for clinical cases, access detailed information about orderable genetic tests, interpret test results, and more.</p><p>More at https://attendee.gotowebinar.com/register/8452228815737989634</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/2261/best-book-titles-for-learning-bionformatics</guid>
	<pubDate>Tue, 13 Aug 2013 17:31:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/2261/best-book-titles-for-learning-bionformatics</link>
	<title><![CDATA[Best book Titles for Learning Bionformatics]]></title>
	<description><![CDATA[<p>Nothing can add to our intellect more than reading a book. &nbsp;In books, we can experience new things that we would not normally be able to experience. It is proved that books can change our lives and other people&rsquo;s lives. Reading can make us more intelligent, updated, imaginative. Without reading we wouldn&rsquo;t know anything that we know today. There are several book, online and offile to read and I can't mentioned all of them here in the list. Therefore, I mentioned some bioinformatics and its related books in subgroups. Hope you will like the list.&nbsp;</p><p>Sequence Analysis and General Bioinformatics</p><ul>
<li>BLAST, Ian Korf, Mark Yandell, Joseph Bedell, 2003, O'Reilly</li>
<li>Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases, Scott Markel, Darryl Leon, 2003, O'Reilly</li>
<li>Bioinformatics for Geneticists, Michael Barnes, Ian C Gray (Editors), 2003, John Wiley &amp; Sons</li>
<li>Bioinformatics for Dummies, Jean-Michel Claverie, Cedric Notredame, 2003, John Wiley &amp; Sons</li>
<li>Mathematics of Genome Analysis, Jerome K. Percus, 2002, Cambridge Univ Press</li>
<li>Bioinformatics Computing, Bryan P. Bergeron, 2002, Prentice Hall</li>
<li>Evolutionary Computation in Bioinformatics, Gary B. Fogel, David W. Corne (Editors), 2002, Morgan Kaufmann</li>
<li>Introduction to Bioinformatics, Arthur M. Lesk, 2002, Oxford University Press</li>
<li>Instant Notes in Bioinformatics, D.R. Westhead, J. H. Parish, R.M. Twyman, 2002, Bios Scientific Pub</li>
<li>Fundamental Concepts of Bioinformatics, Dan E. Krane, Michael L. Raymer, Michaeel L. Raymer, Elaine Nicpon Marieb, 2002, Benjamin/Cummings</li>
<li>Essentials of Genomics and Bioinformatics, C. W. Sensen (Editor), 2002, John Wiley &amp; Sons</li>
<li>Current Topics in Computational Molecular Biology (Computational Molecular Biology), Tao Jiang, Ying Xu, Michael Zhang (Editors), 2002, MIT Press</li>
<li>Hidden Markov Models for Bioinformatics, Timo Koski, Timo Koskinen, 2001, Kluwer Academic Publishers</li>
<li>Bioinformatics: From Genomes to Drugs, Thomas Lengauer (Editor), 2001, John Wiley &amp; Sons</li>
<li>Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health), Warren Ewens, Gregory Grant, 2001, Springer Verlag</li>
<li>Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, Second Edition, Andreas D. Baxevanis, B. F. Francis Ouellette, 2001, Wiley-Interscience</li>
<li>Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning), Pierre Baldi, Soren Brunak, Sren Brunak, 2001, MIT Press</li>
<li>Introduction to Bioinformatics, T eresa Attwood, David Parry-Smith, 2001, Prentice Hall</li>
<li>Bioinformatics: A Primer, Charles Staben, 2001, Jones &amp; Bartlett Pub</li>
<li>Data Analysis and Classification for Bioinformatics, Arun Jagota, 2000, AKJ Academics</li>
<li>Bioinformatics: Sequence and Genome Analysis, David W. Mount, 2001, Cold Spring Harbor Laboratory Press</li>
<li>Bioinformatics: A Biologist's Guide to Biocomputing and the Internet, Stuart M. Brown, 2000, Eaton Pub Co</li>
<li>Bioinformatics: Sequence, Structure and Databanks: A Practical Approach (The Practical Approach Series, 236), Des Higgins (Editor), Willie Taylor (Editor), 2000, Oxford Univ Press</li>
<li>Neural Networks and Genome Informatics, Cathy H. Wu, Jerry W. McLarty, 2000, Elsevier Science</li>
<li>Computational Molecular Biology: An Introduction (Wiley Series in Mathematical and Computational Biology), Peter Clote and Rolf Backofen, 2000, John Wiley &amp; Sons</li>
<li>Computational Molecular Biology: An Algorithmic Approach, Pavel A. Pevzner, 2000, MIT Press</li>
<li>Post-Genome Informatics, Minoru Kanehisa, 2000, Oxford Univ Press</li>
<li>Mathematical and Computational Biology: Computational Morphogenesis, Hierarchical Complexity, and Digital Evolution, Chrystopher L. Nehaniv, 1999, American Mathematical Society</li>
<li>Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications, Jason T. L. Wang, Bruce A. Shapiro, Dennis Elliott Shasha (Editors), 1999, Oxford Univ Press</li>
<li>Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison, David Sankoff and Joseph Kruskal (Editors), 1999, Cambridge University Press</li>
<li>Bioinformatics Basics: Applications in Biological Science and Medicine, Hooman Rashidi, 1999, CRC Press</li>
<li>Bioinformatics: Methods and Protocols (Methods in Molecular Biology, Vol 132), Stephen Misener and Stephen A. Krawetz (Editors),1999, Humana Press</li>
<li>Bioinformatics: Databases and Systems, Stanley Letovsky (Editor),1999, Kluwer Academic Publishers</li>
<li>Computational Molecular Biology, P. Green, 1998, Blackwell Science Inc.</li>
<li>Computational Methods in Molecular Biology (New Comprehensive Biochemistry, V. 32), Steven L. Salzberg, David B. Searls, Simon Kasif (Editors), 1998, Elsevier Science Ltd.</li>
<li>Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Richard Durbin, S. Eddy, A. Krogh, G. Mitchison, 1998, Cambridge University Press</li>
<li>Guide to Human Genome Computing, M. J. Bishop (Editor), 1998, Academic Press</li>
<li>Introduction to Computational Molecular Biology, Joao Meidanis, Joao C. Setabal, 1997, PWS Pub. Co.</li>
<li>Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology, Dan Gusfield, 1997, Cambridge University Press</li>
<li>Sequence Data Analysis Guidebook, Simon R. Swindell (Editor), 1997, Humana Press</li>
<li>High Performance Computational Methods for Biological Sequence Analysis, Tieng K. Yap, Ophir Frieder, Robert L. Martino, 1996, Kluwer Academic Pub.</li>
<li>Computer Methods for Macromolecular Sequence Analysis, Methods in Enzymology, volume 266, Russell F. Doolittle (Editor), 1996, Academic Press</li>
<li>DNA and Protein Sequence Analysis: A Practical Approach (Practical Approach Series , No 171), 1996, M. J. Bishop and C. J. Rawlings (Editors), 1996, IRL Press</li>
<li>Molecular Bioinformatics: Algorithms and Applications, Steffen Schulze-Kremer, 1995, Walter De Gruyter</li>
<li>Introduction to Computational Biology - Maps, sequences and genomes, Michael S. Waterman, 1995, Chapman &amp; Hall</li>
<li>Computer Analysis of Sequence Data, Annette M. Griffin and Hugh G. Griffin (Editors), 1994, Humana Press</li>
<li>Artificial Intelligence and Molecular Biology, Lawrence Hunter (Editor), 1993, AAAI Press</li>
<li>Sequence Analysis Primer, Michael Gribskov and John Devereux (Editors), 1992, Oxford University Press</li>
<li>Mathematical Methods of Analysis of Biopolymer Sequences (Dimacs Series in Discrete Mathematics and Theoretical Computer Science ; Volume 8), S. G. Gindikin, 1992, American Mathematical Society</li>
<li>Mathematical Methods for DNA Sequences, Michael S. Waterman (Editor), 1989, CRC Press</li>
</ul><p>Programming Books for Bioinformatics</p><ul>
<li>Mastering Perl for Bioinformatics, James D. Tisdall, 2003, O'Reilly</li>
<li>Genomic Perl: From Bioinformatics Basics to Working Code, Rex A. Dwyer, 2002, Cambridge University Press</li>
<li>Beginning Perl for Bioinformatics, James Tisdall, 2001, O'Reilly</li>
<li>Developing Bioinformatics Computer Skills, Cynthia Gibas, Per Jambeck, 2001, O'Reilly</li>
</ul><p>General Genomics</p><ul>
<li>Functional Microbial Genomics (Volume 33), Brendan Wren, Nick Dorrell, 2003, Academic Press</li>
<li>Discovering Genomics, Proteomics, and Bioinformatics, A. Malcolm Campbell, Laurie J. Heyer, 2002, Benjamin/Cummings</li>
<li>Genomes, Terence A. Brown, 2002, John Wiley &amp; Sons</li>
<li>Essentials of Medical Genomics, Stuart M. Brown , 2002, John Wiley &amp; Sons</li>
<li>A Primer of Genome Science, Greg Gibson, Spencer V. Muse, 2002, Sinauer Associates</li>
<li>Pathogen Genomics: Impact on Human Health, Karen Joy, Phd Shaw (Editors), 2002, Humana Press</li>
<li>Genomics, John E. Antonopoulos, 2000, Xlibris Corporation</li>
<li>Genomics and Proteomics: Functional and Computational Aspects, Sandor Suhai (Editor), 2000, Plenum Pub Corp</li>
<li>Functional Genomics: A Practical Approach (The Practical Approach Series, 235), S. Hunt and F. Livesey (Editors), 2000, Oxford Univ Press</li>
<li>Human Molecular Genetics, Andrew P. Read, Tom Strachan 1999, BIOS Scientific Publishers Ltd.</li>
<li>Genomics: The Science and Technology Behind the Human Genome Project, Charles R. Cantor and Cassandra L. Smith, 1999, John Wiley &amp; Sons</li>
<li>Cells: A Laboratory Manual, 3 volumes, David L. Spector, Robert D. Goldman, Leslie A. Leinwand, 1998, Cold Spring Harbor Laboratory Press</li>
<li>Genome Analysis: A Laboratory Manual, 4 volumes, Bruce Birren, et al. (Editors), 1997, Cold Spring Harbor Laboratory Press</li>
<li>The Human Genome Project, N. G. Cooper (Editor), 1994, University Science Books</li>
</ul><p>Comparative Genomics</p><ul>
<li>Handbook of Comparative Genomics: Principles and Methodology, Cecilia Saccone, Graziano Pesole, 2003, Wiley-Liss</li>
<li>Sequence - Evolution - Function: Computational Approaches in Comparative Genomics, Eugene V. Koonin, Michael Y. Galperin, 2002, Kluwer Academic Publishers</li>
<li>Comparative Genomics - Empirical and Analytical Approaches to Gene Order Dynamics, Map Alignment and the Evolution of Gene Families, David Sankoff and Joseph H. Nadeau, 2000, Kluwer Academic Pub</li>
<li>Comparative Genomics, Melody Clark (Editor), 2000, Kluwer Academic Pub</li>
</ul><p>Proteomics</p><ul>
<li>Proteins and Proteomics: A Laboratory Manual, Richard J. Simpson (Editor), Cold Spring Harbor Laboratory</li>
<li>Proteomics in Practice: A Laboratory Manual of Proteome Analysis , Reiner Westermeier, Tom Naven, 2002, John Wiley &amp; Sons</li>
<li>Posttranslational Modifications of Proteins: Tools for Functional Proteomics (Methods in Molecular Biology, Vol 194) , Christoph Kannicht (Editor), 2002, Humana Press</li>
<li>Peptide Arrays on Membrane Supports: Synthesis and Applications (Springer Lab Manual), Joachim Koch, Michael Mahler (Editors), 2002, Springer Verlag</li>
<li>Proteomics , Timothy Palzkill, 2002, Kluwer Academic Publishers</li>
<li>Introduction to Proteomics: Tools for the New Biology , Daniel C. Liebler (Editor), 2001, Humana Press</li>
<li>Proteome Research: Mass Spectrometry (Principles and Practice) , P. James (Editor), 2001, Springer Verlag</li>
<li>Interpreting Protein Mass Spectra: A Comprehensive Resource , A. Peter Snyder, 2000, American Chemical Society</li>
<li>Protein Sequencing and Identification Using Tandem Mass Spectrometry , Michael Kinter, Nicholas E. Sherman, 2000, Wiley-Interscience</li>
<li>From Genome to Proteome: Advances in the Practice and Application of Proteomics, Michael J. Dunn (Editor), 2000, Vch Verlagsgesellschaft Mbh</li>
<li>Proteomics: From Protein Sequence to Function, S. Pennington (Editor), M. Dunn (Editor), 2000, Springer Verlag</li>
<li>Proteome Research: Two-Dimensional Gel Electrophoresis and Detection Methods (Principles and Practice), T. Rabilloud (Editor), 2000, Springer Verlag</li>
<li>Proteome and Protein Analysis, R. M. Kamp, D. Kyriakidis, th Choli-Papadopoulou (Editor), 1999, Springer Verlag</li>
<li>Proteome Research: New Frontiers in Functional Genomics, M. R. Wilkins, et al. (Editors), 1997, Springer Verlag</li>
</ul><p>Protein Structure</p><ul>
<li>Structural Bioinformatics, Philip E. Bourne, Helge Weissig (Editors), 2003, John Wiley &amp; Sons</li>
<li>Protein Structure Prediction: Bioinfomatic Approach, I.F. Tsigelny, 2002, International University Line</li>
<li>Introduction to Protein Architecture: The Structural Biology of Proteins, Arthur M. Lesk, 2001, Oxford University Press</li>
<li>Protein Structure Prediction: Methods and Protocols, David M. Webster (Editor), 2000, Humana Press</li>
<li>Introduction to Protein Structure, Carl-Ivar Branden, John Tooze, 1999, Garland Publishing</li>
<li>Structure and Mechanism in Protein Science: A Guide to Enzyme Catalysis and Protein Folding, Alan Fersht, 1999, Freeman</li>
</ul><p>Pharmacogenomics</p><ul>
<li>Pharmacogenomics: Social, Ethical, and Clinical Dimensions, Mark A. Rothstein (Editor), 2003, Wiley-Liss</li>
<li>Pharmacogenomics: The Search for Individualized Therapies, Julio Licinio, Ma-Li Wong (Editors), 2002, John Wiley &amp; Sons</li>
<li>Pharmacogenomics, Werner Kalow, Urs A. Meyer, Rachel Tyndale (Editors), 2001, Marcel Dekker</li>
<li>Pharmacogenetics and Pharmcogenomics: Recent Conceptual and Technical Advances (Pharmacology, Volume 61, Number 3, 2000), Elliot S. Vesell (Editor), 2000, S. Karger Publishing</li>
<li>Pharmacogenetics, Wendell Weber, 1997, Oxford University Press</li>
</ul><p>DNA Microarrays</p><ul>
<li>Statistical Analysis of Gene Expression Microarray Data, T. P. Speed (Editor), 2003, CRC Press</li>
<li>Microarray Gene Expression Data Analysis: A Beginner's Guide, Helen C. Causton, John Quackenbush, Alvis Brazma, 2003, Blackwell Publishers</li>
<li>The Analysis of Gene Expression Data (Statistics for Biology and Health), G. Parmigiani, E. S. Garrett, R. A. Irizarry, S. Zeger , Graeme Clark (Editors), 2003, Springer Verlag</li>
<li>A Practical Approach to Microarray Data Analysis, Daniel P. Berrar, Werner Dubitzky, Martin Granzow (Editors), 2002, Kluwer Academic Publishers</li>
<li>DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling, Pierre Baldi, G. Wesley Hatfield, 2002, Cambridge University Press</li>
<li>DNA Microarrays: A Molecular Cloning Manual, David Bowtell, Joseph Sambrook (Editors), 2002, Cold Spring Harbor Laboratory</li>
<li>DNA Array Image Analysis: Nuts &amp; Bolts, Gerda Kamberova, Shishir Shah, 2002, DNA Press</li>
<li>Microarray Analysis, Mark Schena, 2002, John Wiley &amp; Sons</li>
<li>A Biologist's Guide to Analysis of DNA Microarray Data, Steen Knudsen, 2002, John Wiley &amp; Sons</li>
<li>Microarrays for an Integrative Genomics (Computational Molecular Biology), Isaac S. Kohane, Alvin Kho, Atul J. Butte, 2002, MIT Press</li>
<li>Microarrays for the Neurosciences: An Essential Guide (Cellular and Molecular Neuroscience), Daniel H. Geschwind, Jeffrey P. Gregg (Editors), 2002, MIT Press</li>
<li>DNA Microarrays: Gene Expression Applications, Bertrand Jordan (Editor), 2001, Springer Verlag</li>
<li>DNA Arrays: Methods and Protocols (Methods in Molecular Biology, Volume 170), Jang B. Rampal (Editor), 2001, Humana Press</li>
<li>DNA Arrays: Technologies and Experimental Strategies, Elena V. Grigorenko (Editor), 2001, CRC Press</li>
<li>Microarray Biochip Technology, Mark Schena (Editor), 2000, Eaton Pub</li>
<li>Expression Genetics: Accelerated and High-Throughput Methods (Biotechniques Update Series), Michael McClelland (Editor), Arthur B. Pardee (Editor), 1999, Eaton Pub</li>
<li>DNA Microarrays: A Practical Approach (Practical Approach Series 205), Mark Schena (Editor), 1999, Oxford Univ Press</li>
<li>cDNA Preparation and Characterization (Methods in Enzymology Volume 303), S.M. Weissman (Editor), 1999, Academic Press</li>
</ul><p>Systems Biology, Genetic and Biochemical Network</p><ul>
<li>Handbook of Graphs and Networks : From the Genome to the Internet, Stefan Bornholdt, Heinz Georg Schuster (Editors), 2003, Vch Verlagsgesellschaft Mbh</li>
<li>Computational Cell Biology, Christopher Fall, Eric Marland, John Wagner, John Tyson (Editors), 2002, Springer Verlag</li>
<li>Gene Regulation and Metabolism: Post-Genomic Computational Approaches (Computational Molecular Biology), Julio Collado-Vides, Ralf Hofestadt (Editors), 2002, MIT Press</li>
<li>Foundations of Systems Biology, Hiroaki Kitano (Editor), 2001, MIT Press</li>
<li>Genomic Regulatory Systems: Development and Evolution, Eric H. Davidson , 2001, Academic Press</li>
<li>Genes &amp; Signals, Mark Ptashne, Alexander Gann, 2001, Cold Spring Harbor Laboratory</li>
<li>Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology), James M. Bower and Hamid Bolouri (Editors), 2001, MIT Press</li>
<li>Protein-Protein Interactions: A Molecular Cloning Manual, Erica Golemis (Editor), 2001, Cold Spring Harbor Laboratory</li>
<li>Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists, Eberhard O. Voit, 2000, Cambridge University Press</li>
<li>Mathematical Physiology, James P. Keener, James Sneyd, 1998, Springer Verlag</li>
</ul><p>&nbsp;</p><p>DNA Sequencing</p><ul>
<li>DNA Sequencing: From Experimental Methods to Bioinformatics (Introduction to Biotechniques Series), Luke Alphey, 1997, Springer Verlag</li>
<li>Automated DNA sequencing and analysis, Adams M.D., Fields C., Venter J.C. (Editors), 1994, Academic Press</li>
</ul><p>&nbsp;</p><p>Apart from above mentioned books, you can also find some useful books links at following mentioned URLs:</p><p>&nbsp;</p><p><a href="http://www.amazon.com/Biological-Sequence-Analysis-Probabilistic-Proteins/dp/0521629713">http://www.amazon.com/Biological-Sequence-Analysis-Probabilistic-Proteins/dp/0521629713</a></p><p><a href="http://www.amazon.com/Bioinformatics-Genes-Proteins-Computers-Advanced/dp/1859960545">http://www.amazon.com/Bioinformatics-Genes-Proteins-Computers-Advanced/dp/1859960545</a></p><p><a href="http://www.amazon.com/Introduction-Bioinformatics-Algorithms-Computational-Molecular/dp/0262101068">http://www.amazon.com/Introduction-Bioinformatics-Algorithms-Computational-Molecular/dp/0262101068</a></p><p><a href="http://books.google.no/books?id=pxSM7R1sdeQC&amp;dq=Pierre+baldi+%2B+bioinformatics&amp;printsec=frontcover&amp;source=bn&amp;hl=en&amp;ei=IoGRS6uCIJT-NYLA8Z0N&amp;sa=X&amp;oi=book_result&amp;ct=result&amp;redir_esc=y#v=onepage&amp;q&amp;f=false">http://books.google.no/books?id=pxSM7R1sdeQC&amp;dq=Pierre+baldi+%2B+bioinformatics&amp;printsec=frontcover&amp;source=bn&amp;hl=en&amp;ei=IoGRS6uCIJT-NYLA8Z0N&amp;sa=X&amp;oi=book_result&amp;ct=result&amp;redir_esc=y#v=onepage&amp;q&amp;f=false</a></p><p><a href="http://www.amazon.com/Statistical-Methods-Bioinformatics-Introduction-Statistics/dp/0387400826">http://www.amazon.com/Statistical-Methods-Bioinformatics-Introduction-Statistics/dp/0387400826</a></p><p>&nbsp;</p><p>If you think your favourite books are not listed then please write it down in comment section for the benefits of other users.&nbsp;Feel free to add many more books in comment section.&nbsp;</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38659/detail-annotation-of-genes</guid>
	<pubDate>Fri, 11 Jan 2019 05:23:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38659/detail-annotation-of-genes</link>
	<title><![CDATA[Detail annotation of genes !]]></title>
	<description><![CDATA[<p>gene_info recalculated daily<br>---------------------------------------------------------------------------<br> tab-delimited<br> one line per GeneID<br> Column header line is the first line in the file.<br> Note: subsets of gene_info are available in the DATA/GENE_INFO<br> directory (described later)<br>---------------------------------------------------------------------------</p>
<p>tax_id:<br> the unique identifier provided by NCBI Taxonomy<br> for the species or strain/isolate</p>
<p>GeneID:<br> the unique identifier for a gene<br> ASN1: geneid</p>
<p>Symbol:<br> the default symbol for the gene<br> ASN1: gene-&gt;locus</p>
<p>LocusTag:<br> the LocusTag value<br> ASN1: gene-&gt;locus-tag</p>
<p>Synonyms:<br> bar-delimited set of unofficial symbols for the gene</p>
<p>dbXrefs:<br> bar-delimited set of identifiers in other databases<br> for this gene. The unit of the set is database:value.<br> Note that HGNC and MGI include 'HGNC' and 'MGI', respectively,<br> in the value part of their identifier. Consequently,<br> dbXrefs for these databases will appear like:<br> HGNC:HGNC:1100<br> This would be interpreted as database='HGNC', value='HGNC:1100'<br> Example for MGI:<br> MGI:MGI:104537<br> This would be interpreted as database='MGI', value='MGI:104537'</p>
<p>chromosome:<br> the chromosome on which this gene is placed.<br> for mitochondrial genomes, the value 'MT' is used.</p>
<p>map location:<br> the map location for this gene</p>
<p>description:<br> a descriptive name for this gene</p>
<p>type of gene:<br> the type assigned to the gene according to the list of options<br> provided in https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/lxr/source/src/objects/entrezgene/entrezgene.asn</p>
<p><br>Symbol from nomenclature authority:<br> when not '-', indicates that this symbol is from a<br> a nomenclature authority</p>
<p>Full name from nomenclature authority:<br> when not '-', indicates that this full name is from a<br> a nomenclature authority</p>
<p>Nomenclature status:<br> when not '-', indicates the status of the name from the <br> nomenclature authority (O for official, I for interim)</p>
<p>Other designations:<br> pipe-delimited set of some alternate descriptions that<br> have been assigned to a GeneID<br> '-' indicates none is being reported.</p>
<p>Modification date:<br> the last date a gene record was updated, in YYYYMMDD format</p>
<p>Feature type:<br> pipe-delimited set of annotated features and their classes or <br> controlled vocabularies, displayed as feature_type:feature_class <br> or feature_type:controlled_vocabulary, when appropriate; derived <br> from select feature annotations on RefSeq(s) associated with the <br> GeneID</p><p>Address of the bookmark: <a href="ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/" rel="nofollow">ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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