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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/45303?offset=90</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45240/pg2-making-pangenome-graphs-easier-to-understand</guid>
	<pubDate>Tue, 18 Aug 2026 04:38:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45240/pg2-making-pangenome-graphs-easier-to-understand</link>
	<title><![CDATA[PG2: Making Pangenome Graphs Easier to Understand]]></title>
	<description><![CDATA[<p>Genomics is moving beyond the traditional approach of studying DNA using a single reference genome. Today, researchers are increasingly using pangenomes, which represent genetic information from multiple genomes and capture a much broader range of genetic diversity.</p><p>However, pangenome graphs can be highly complex, making them difficult to visualize and interpret. A recent study published in BMC Bioinformatics introduces PG2 (PanGenoGrapher), an open-source, web-based tool designed to address this challenge.&nbsp;The source code and user guide are openly available on GitHub at https://github.com/iVis-at-Bilkent/pangenographer. A publicly accessible sample deployment is hosted at http://pg2.cs.bilkent.edu.tr. In addition, a demonstration video illustrating the primary use cases of PG2 is available at https://www.youtube.com/watch?v=yCd7-aGY6CQ.</p><p>PG2 combines advanced graph-layout algorithms with an interactive visualization platform. It allows researchers to explore genomic paths, identify variations, and examine relationships between different parts of a pangenome graph more easily.</p><p>This is important because visualization can play a major role in bioinformatics. When complex genomic information is presented clearly, researchers can more easily identify patterns, understand genetic variation, and generate new biological insights.</p><p>The development of PG2 represents a step toward making pangenome analysis more accessible and intuitive. As genomic datasets continue to grow and graph-based representations become more common, tools like PG2 can help researchers navigate this increasing complexity.</p><p>Ultimately, PG2 demonstrates how combining genomics, graph algorithms, and interactive visualization can make sophisticated biological data easier to understand and analyze.</p><p>Reference: Solun, G. K., Dogrusoz, U., Bing&ouml;l, Z., &amp; Alkan, C. (2026). PG2: algorithms and a web-based tool for effective layout and visual analysis of pangenome graphs. BMC Bioinformatics. DOI: 10.1186/s12859-026-06555-4.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45289/the-atlas-of-nine-billion-possibilities</guid>
	<pubDate>Wed, 09 Sep 2026 02:07:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45289/the-atlas-of-nine-billion-possibilities</link>
	<title><![CDATA[The Atlas of Nine Billion Possibilities]]></title>
	<description><![CDATA[<p>Imagine a book that holds all the instructions for building a human, made up of billions of letters. What if you changed just one letter? Maybe nothing would happen. Or that tiny change could affect how a gene works, quietly shaping a cell&rsquo;s biology or even helping cause disease.</p><p>Scientists face a big challenge with the human genome. They can read its letters, but understanding their roles is much harder. Only about 2 percent of the genome codes for proteins. The rest acts like a huge control panel, deciding when and where genes turn on. With about 9 billion possible single-letter changes, testing them all in a lab just isn&rsquo;t possible.</p><p>So, Google DeepMind asked a new question: what if we could predict what those changes might do?</p><p>This question led to the AlphaGenome Atlas (https://deepmind.google.com/science/alphagenome/atlas?), a detailed map of nearly every possible single-letter change in the human genome. Instead of checking each change one by one, researchers can use the Atlas to spot the ones most likely to matter. The AlphaGenome Variant Impact (AVI) score works like a trail marker, pointing scientists toward the changes worth a closer look.</p><p>This is where the Atlas gets especially useful. Much of the genome lies outside the protein-coding regions, where DNA acts as a switch or controller for genes. AlphaGenome lets researchers explore these areas and see how small changes could affect gene activity.</p><p>An atlas isn't the destination; it's a guide.</p><p>The AlphaGenome Atlas doesn&rsquo;t replace experiments or solve every mystery. Instead, it helps scientists decide where to begin. From billions of possibilities, it turns the vast genetic landscape into something researchers can start to explore.</p><p>There are nine billion possibilities, a vast map, and maybe among them therWith nine billion possibilities and a huge map to explore, there may be clues hidden here to some of medicine&rsquo;s toughest mysteries.</p><p>More at&nbsp;https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/alphagenome-atlas-a-predictive-map-of-every-possible-dna-letter-change-in-the-human-genome/alphagenome-atlas.pdf</p>]]></description>
	<dc:creator>Jitendra Narayan</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/40476/libsdyogen-libibrary-for-comparative-genomics</guid>
	<pubDate>Wed, 25 Dec 2019 01:32:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40476/libsdyogen-libibrary-for-comparative-genomics</link>
	<title><![CDATA[LibsDyogen: Libibrary for comparative genomics]]></title>
	<description><![CDATA[<p>Library of usual classes and functions written in python and used in the Dyogen team for comparative genomics applications.</p>
<p>Collaborative python library used in the<span>&nbsp;</span><a href="http://www.ibens.ens.fr/?rubrique43&amp;lang=fr">DYOGEN team</a>for studying the evolution of gene order in vertebrates.</p>
<p><a href="http://www.ibens.ens.fr/?rubrique43&amp;lang=fr">http://www.ibens.ens.fr/?rubrique43&amp;lang=fr</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/DyogenIBENS/LibsDyogen" rel="nofollow">https://github.com/DyogenIBENS/LibsDyogen</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33909/itol-interactive-tree-of-life</guid>
	<pubDate>Tue, 18 Jul 2017 05:36:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33909/itol-interactive-tree-of-life</link>
	<title><![CDATA[iTOL: Interactive Tree Of Life]]></title>
	<description><![CDATA[<p><strong>Interactive Tree Of Life</strong>&nbsp;is an online tool for the display, annotation and management of phylogenetic trees.</p>
<p>Explore your trees directly in the browser, and annotate them with various types of data.</p>
<p><span>iTOL can easily visualize trees with 50'000 or more leaves. With advanced search capabilities and display of unrooted, circular and regular cladograms or phylograms, exploring and navigating trees of any size is simple.</span></p>
<p>https://itol.embl.de/</p><p>Address of the bookmark: <a href="https://itol.embl.de/" rel="nofollow">https://itol.embl.de/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41899/stay-at-home-revbayes-workshop</guid>
  <pubDate>Sat, 20 Jun 2020 11:53:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Stay-at-Home RevBayes Workshop]]></title>
  <description><![CDATA[
<p>Stay-at-Home RevBayes Workshop<br />Location: Anywhere (online-only event)<br />Dates: 7/13, 2020 to 8/12, 2020<br />Instructors: Joëlle Barido-Sottani, Walker Pett, Josh Justison, Wade Dismukes, Luiza Fabreti, Tracy Heath, Jeremy M. Brown, Rosana Zenil-Ferguson<br />Register: https://iastate.qualtrics.com/jfe/form/SV_02sCYRWbxYK9I5D</p>

<p>Description<br />This free online-only RevBayes workshop will provide an introduction to the theory and use of RevBayes, with a focus on (1) tree inference from molecular data, (2) analyses combining fossil and extant taxa, and (3) evaluating MCMC performance, with advanced topics including assessing model adequacy and macroevolutionary analyses. Additional topics may be added depending on the interests of selected participants. The format will be a combination of interactive video sessions (via Zoom or similar tools), real-time discussions over Slack, self-guided tutorials, and pre-recorded videos.</p>

<p>The initial session will resolve technical issues and present the basics of using RevBayes. Participants will then be expected to work through several tutorials on their own schedule, with the help of pre-recorded materials. A Slack forum will be open for questions and issues. The workshop will conclude with several online Q&amp;A sessions with the instructors. The dates for the interactive sessions are currently tentative and may be adjusted depending on the schedules of the participants and instructors.</p>

<p>We are hoping to identify up to 15 participants for this online course. While we hope we are able to accommodate everyone who applies, we realize that this may not be possible because of time-zones and availability. If the number of applicants exceeds our capacity, we hope to organize a second round of sessions later in the year. Participants will not be charged for the course, but we will request that they commit to completing the tutorials and attending a majority of interactive sessions.</p>

<p>To apply to this course, please go to the registration form and submit your application by July 6, 2020.</p>

<p>More at https://revbayes.github.io/workshops/online2020.html</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40946/free-genomics-data</guid>
	<pubDate>Fri, 07 Feb 2020 14:08:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40946/free-genomics-data</link>
	<title><![CDATA[Free Genomics data !]]></title>
	<description><![CDATA[<p><span>The specimens were collected by the Oxford Wytham Woods and Edinburgh Lohse lab teams. DNA extraction and sequencing was carried out by the Sanger Institute Scientific Operations teams. Assemblies were carried out by the Tree of Life team (Shane McCarthy) and colleagues in Pacific Biosciences (Jonas Korlach).</span></p>
<p><a href="https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/">https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/</a></p><p>Address of the bookmark: <a href="https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/" rel="nofollow">https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43916/understanding-dump-files-from-ncbi-taxonomy-database</guid>
	<pubDate>Fri, 15 Jul 2022 04:29:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43916/understanding-dump-files-from-ncbi-taxonomy-database</link>
	<title><![CDATA[Understanding DUMP files from NCBI Taxonomy database !]]></title>
	<description><![CDATA[<p>*.dmp files are bcp-like dump from GenBank taxonomy database</p><p>General information.</p><p>Field terminator is "\t|\t"</p><p>Row terminator is "\t|\n"</p><p>&nbsp;</p><p>nodes.dmp file consists of taxonomy nodes. The description for each node includes the following</p><p>fields:</p><p>tax_id -- node id in GenBank taxonomy database</p><p>&nbsp; parent tax_id -- parent node id in GenBank taxonomy database</p><p>&nbsp; rank -- rank of this node (superkingdom, kingdom, ...)&nbsp;</p><p>&nbsp; embl code -- locus-name prefix; not unique</p><p>&nbsp; division id -- see division.dmp file</p><p>&nbsp; inherited div flag&nbsp; (1 or 0) -- 1 if node inherits division from parent</p><p>&nbsp; genetic code id -- see gencode.dmp file</p><p>&nbsp; inherited GC&nbsp; flag&nbsp; (1 or 0) -- 1 if node inherits genetic code from parent</p><p>&nbsp; mitochondrial genetic code id -- see gencode.dmp file</p><p>&nbsp; inherited MGC flag&nbsp; (1 or 0) -- 1 if node inherits mitochondrial gencode from parent</p><p>&nbsp; GenBank hidden flag (1 or 0)&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; -- 1 if name is suppressed in GenBank entry lineage</p><p>&nbsp; hidden subtree root flag (1 or 0) &nbsp; &nbsp; &nbsp; -- 1 if this subtree has no sequence data yet</p><p>&nbsp; comments -- free-text comments and citations</p><p>&nbsp;</p><p>Taxonomy names file (names.dmp):</p><p>tax_id -- the id of node associated with this name</p><p>name_txt -- name itself</p><p>unique name -- the unique variant of this name if name not unique</p><p>name class -- (synonym, common name, ...)</p><p>&nbsp;</p><p>Divisions file (division.dmp):</p><p>division id -- taxonomy database division id</p><p>division cde -- GenBank division code (three characters)</p><p>division name -- e.g. BCT, PLN, VRT, MAM, PRI...</p><p>comments</p><p>&nbsp;</p><p>Genetic codes file (gencode.dmp):</p><p>genetic code id -- GenBank genetic code id</p><p>abbreviation -- genetic code name abbreviation</p><p>name -- genetic code name</p><p>cde -- translation table for this genetic code</p><p>starts -- start codons for this genetic code</p><p>&nbsp;</p><p>Deleted nodes file (delnodes.dmp):</p><p>tax_id -- deleted node id</p><p>&nbsp;</p><p>Merged nodes file (merged.dmp):</p><p>old_tax_id&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; -- id of nodes which has been merged</p><p>new_tax_id&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; -- id of nodes which is result of merging</p><p>Citations file (citations.dmp):</p><p>cit_id -- the unique id of citation</p><p>cit_key -- citation key</p><p>pubmed_id -- unique id in PubMed database (0 if not in PubMed)</p><p>medline_id -- unique id in MedLine database (0 if not in MedLine)</p><p>url -- URL associated with citation</p><p>text -- any text (usually article name and authors).</p><p>-- The following characters are escaped in this text by a backslash:</p><p>-- newline (appear as "\n"),</p><p>-- tab character ("\t"),</p><p>-- double quotes ('\"'),</p><p>-- backslash character ("\\").</p><p>taxid_list -- list of node ids separated by a single space</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4590/tigers-genome-sequenced</guid>
	<pubDate>Tue, 17 Sep 2013 16:48:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4590/tigers-genome-sequenced</link>
	<title><![CDATA[Tigers genome sequenced]]></title>
	<description><![CDATA[<p>Fifteen scientists led by Dr Jong Bhak of Genome Research Foundation, South Korea, decoded as many as 3 billion nucleotides (organic molecules that form the basic building blocks of nucleic acids, such as DNA). They identified 20,000 genes related to various functions of the tiger.&nbsp;</p><p>The biggest and perhaps most fearsome of the world's big cats, the tiger, shares 95.6 percent of its DNA with humans' cute and furry companions, domestic cats.</p><p>The new research showed that big cats have genetic mutations that enabled them to be carnivores. The team also identified mutations that allow snow leopards to thrive at high altitudes.</p><p>Reference:</p><p><a href="http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690">http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690</a></p><p><a href="http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms">http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms</a></p><p>Paper:</p><p><a href="http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html">http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34443/opera-an-optimal-genome-scaffolding-program</guid>
	<pubDate>Mon, 27 Nov 2017 10:18:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34443/opera-an-optimal-genome-scaffolding-program</link>
	<title><![CDATA[Opera: An optimal genome scaffolding program]]></title>
	<description><![CDATA[<p><span>Opera (Optimal Paired-End Read Assembler) is a sequence assembly program (</span><a href="http://en.wikipedia.org/wiki/Sequence_assembly" target="_blank">http://en.wikipedia.org/wiki/Sequence_assembly&nbsp;<img src="https://a.fsdn.com/con/img/icons/external_asset.png" alt="image" style="border: 0px;"></a><span>). It uses information from paired-end or long reads to optimally order and orient contigs assembled from shotgun-sequencing reads.</span><br><br><span>An updated version called OPERA-LG has been re-engineered with features for the assembly of large and complex genomes.</span><br><br><span>Song Gao, Denis Bertrand, Burton K. H. Chia and Niranjan Nagarajan. OPERA-LG: efficient and exact scaffolding of large, repeat-rich eukaryotic genomes with performance guarantees. Genome Biology, May 2016, doi: 10.1186/s13059-016-0951-y.</span><br><br><span>Song Gao, Wing-Kin Sung, Niranjan Nagarajan. Opera: reconstructing optimal genomic scaffolds with high-throughput paired-end sequences. Journal of Computational Biology, Sept. 2011, doi:10.1089/cmb.2011.0170.</span></p>
<p><span>https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0951-y</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/operasf/" rel="nofollow">https://sourceforge.net/projects/operasf/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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