<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42810?offset=1140</link>
	<atom:link href="https://bioinformaticsonline.com/related/42810?offset=1140" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5702/research-fellow-in-bioinformatics-queens-university-belfast-institute-for-global-food-security-school-of-biological-sciences</guid>
  <pubDate>Thu, 17 Oct 2013 04:33:02 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Fellow in Bioinformatics @  Queen's University Belfast -Institute for Global Food Security, School of Biological Sciences]]></title>
  <description><![CDATA[
<p>Ref: 13/102900</p>

<p>Available immediately until 30th November 2015, to work on the development of bioinformatics approaches to aid analysis of data derived from the metabolomic profiling of biological matrices. The successful applicant will lead research activities on an FP7 funded EU-wide collaborative project aimed at establishing biomarker-based strategies for high throughput diagnostic screening. Key tasks will involve multivariate analysis of large datasets, bioinformatic-based selection and validation of identified markers, construction of metabolomic spectral profile databases and development of machine learning/database searching approaches amenable to analytical screening techniques. This position will offer the opportunity to travel and undertake work with project collaborators based in the Republic of Ireland and Europe.</p>

<p>Informal enquiries may be directed to Dr Terry McGrath, email: terry.mcgrath@qub.ac.uk.</p>

<p>Anticipated interview date: Thursday 31st October 2013<br />Salary scale: £30,424 – £39,649 per annum (including contribution points)<br />Closing date: Monday 21st October 2013  </p>

<p>Telephone (028) 90973044 FAX: (028) 90971040 or e-mail on personnel@qub.ac.uk</p>

<p>The University is committed to equality of opportunity and to selection on merit.  It therefore welcomes applications from all sections of society and particularly welcomes applications from people with a disability. </p>

<p>Fixed term contract posts are available for the stated period in the first instance but in particular circumstances may be renewed or made permanent subject to availability of funding.</p>

<p>More @ https://hrwebapp.qub.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=5616943npO&amp;WVID=6273090Lgx&amp;LANG=USA</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44741/bioinformatician-in-pipeline-development</guid>
  <pubDate>Tue, 17 Dec 2024 23:43:54 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatician in pipeline development]]></title>
  <description><![CDATA[
<p>Are you interested in working with pipeline development in bioinformatics, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a position as Bioinformatician in pipeline development at Uppsala University.</p>

<p>National Bioinformatics Infrastructure Sweden (NBIS) (nbis.se) plays an important role in advancing life science research in Sweden by providing expert support and developing cutting-edge bioinformatics infrastructure. Operating as a truly national initiative, NBIS employs more than 120 bioinformaticians, system developers, and data stewards across multiple locations in Sweden. It serves as the bioinformatics platform at SciLifeLab, a national resource that facilitates research in molecular biosciences by offering access to state-of-the-art technologies and technical expertise. With strong ties to data-producing facilities and ongoing collaborations with leading research groups, NBIS is ideally positioned to support world-class bioinformatics analyses. Furthermore, NBIS is the Swedish node in ELIXIR, the European infrastructure for biological information.</p>

<p>NBIS is seeking an experienced bioinformatician to support both Swedish and international projects. As part of our dynamic team, you will work closely with researchers to process large-scale biological data and contribute to advancing our data analysis infrastructure. Strong problem-solving skills, attention to detail, and the ability to troubleshoot complex bioinformatics pipelines are essential for success in this role. Flexibility and a willingness to learn are also important, as NBIS continually adapts to meet the evolving needs of the Swedish research community.</p>

<p>More at https://www.uu.se/en/about-uu/join-us/jobs-and-vacancies/job-details?query=778701</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5947/jrf-national-jalma-institute-of-leprosy-and-other-mycobacterial-diseases</guid>
  <pubDate>Mon, 28 Oct 2013 10:42:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF @ NATIONAL JALMA INSTITUTE OF LEPROSY AND OTHER MYCOBACTERIAL DISEASES]]></title>
  <description><![CDATA[
<p>NATIONAL JALMA INSTITUTE OF LEPROSY AND OTHER MYCOBACTERIAL DISEASES</p>

<p>(INDIAN COUNCIL OF MEDICAL RESEARCH)</p>

<p>P.O BOX 101,<br />Dr. M. Miyazaki Marg,<br />Tajganj, Agra - 282001</p>

<p>Applications are invited for a walk-in interview to be held in the Seminar Hall of the on 15th November, 2013, 9:30 am for temporary positions of JRF, Lab Technician and Field attendant in a ICMR funded project entitled "Elucidating the strain differentiation and transmission dynamics of M. leprae through simple sequence repeats ISSR-PCR marker"</p>

<p>1. JRF (one Post)</p>

<p>    Essential qualification: Candidates with M.Sc/IVI.Tech or equivalent degree in any life science related subjects with UGC-CSIR/ICMR/DBT-Net qualified</p>

<p>    Desirable qualification: Experience in Molecular Biology/Computational Biology will be preferred.</p>

<p>    Age. Maximum 28 years as on 11.11.2013. Age relaxation as per GOI rules.</p>

<p>    Emoluments: Rs. 6,000 + 20% HRA per Month</p>

<p>2. Lab Technician (One Post)</p>

<p>    Essential Qualification: 12th with DMLT/B.SCA4.SC in Life sciences</p>

<p>    Desirable qualification: Experience in Molecular Biology/Computational Biology will be preferred.</p>

<p>    Age: Maximum 30 years as on 11.11.2013. Age relaxation as per GOI rules.</p>

<p>    Emoluments: Rs13,760/ Per Month</p>

<p>3. Field Attendant (One Post)</p>

<p>Essential Qualification: 10th Pass</p>

<p>Desirable Qualification: Experience in field work</p>

<p>Age: Maximum 28 years as on 11.11.2013. Age relaxation as per GOI rules.</p>

<p>Emoluments: Rsl2,040l Per Month</p>

<p>Terms: posts are purely temporary. Appointment will be initially made for a period of one (01) year and may be extended further based on the performance of the candidate up to completion of the project.</p>

<p>Application &amp; Selection procedure: candidates have to appear in the walk-in-interview in person along with an application/CV on plain paper giving details of at educational qualificationq experience and submit photocopies of relevant documents at the time of interview. Selection will be based on the performance of the candidate in the interview' Candidates will not be sent any interview call letter separately. No TA/DA will be paid to the candidate for appearing in the interview. selection is not possible without appearing in the interview. All candidates must report by 9:00am on the date of interview. Advance copy of CV may be sent to m.sarathipartha@gmail.com</p>

<p>Advertisement: http://www.jalma-icmr.org.in/P_S_M_advertisment.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44760/the-future-of-bioinformatics-innovations-and-opportunities</guid>
	<pubDate>Mon, 20 Jan 2025 12:44:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44760/the-future-of-bioinformatics-innovations-and-opportunities</link>
	<title><![CDATA[The Future of Bioinformatics: Innovations and Opportunities]]></title>
	<description><![CDATA[<p>Bioinformatics, the interdisciplinary field that merges biology, computer science, and statistics, has transformed the way we understand biological systems. As we stand at the cusp of a new era in scientific discovery, the future of bioinformatics promises even greater advancements, powered by cutting-edge technologies and a growing understanding of life&rsquo;s complexities.</p><h4>1. Big Data and Bioinformatics</h4><p>The exponential growth in biological data, driven by advancements in sequencing technologies and high-throughput experiments, has made bioinformatics an indispensable tool. By 2030, we anticipate:</p><ul>
<li>
<p><strong>Petabyte-Scale Data Management</strong>: Enhanced storage solutions and cloud computing platforms will allow researchers to handle the vast amounts of data generated from omics studies, including genomics, transcriptomics, and proteomics.</p>
</li>
<li>
<p><strong>AI and Machine Learning Integration</strong>: Sophisticated algorithms will uncover patterns and relationships in large datasets, enabling predictions about gene function, disease susceptibility, and therapeutic outcomes.</p>
</li>
</ul><h4>2. Personalized Medicine and Genomics</h4><p>Bioinformatics will play a pivotal role in tailoring healthcare to individual patients. Key developments include:</p><ul>
<li>
<p><strong>Whole-Genome Sequencing in Clinics</strong>: The decreasing cost of sequencing will make it routine in medical diagnostics, enabling personalized treatment plans based on an individual&rsquo;s genetic makeup.</p>
</li>
<li>
<p><strong>Drug Repurposing and Development</strong>: Computational tools will identify potential new uses for existing drugs, accelerating the development of targeted therapies.</p>
</li>
</ul><h4>3. Advancing Computational Tools</h4><p>The future will see the development of more user-friendly and powerful bioinformatics tools:</p><ul>
<li>
<p><strong>Graph-Based Approaches</strong>: Enhanced algorithms for analyzing complex biological networks, such as protein-protein interaction maps.</p>
</li>
<li>
<p><strong>Visualization Tools</strong>: Intuitive software for visualizing multi-dimensional data, enabling researchers to interpret findings more effectively.</p>
</li>
</ul><h4>4. Synthetic Biology and Systems Biology</h4><p>Bioinformatics will continue to drive progress in synthetic and systems biology by:</p><ul>
<li>
<p><strong>Gene Circuit Design</strong>: Leveraging computational models to design and simulate synthetic biological systems.</p>
</li>
<li>
<p><strong>Understanding Cellular Pathways</strong>: Integrating multi-omics data to model cellular processes with unprecedented accuracy.</p>
</li>
</ul><h4>5. Bioinformatics in Agriculture and Environmental Science</h4><p>Beyond healthcare, bioinformatics will revolutionize agriculture and environmental conservation:</p><ul>
<li>
<p><strong>Crop Improvement</strong>: Genomic studies will help develop high-yield, disease-resistant, and climate-resilient crops.</p>
</li>
<li>
<p><strong>Microbial Ecology</strong>: Metagenomics will enhance our understanding of microbial communities, aiding in bioremediation and ecosystem management.</p>
</li>
</ul><h4>6. Democratization of Bioinformatics</h4><p>Open-source software and accessible education will broaden participation in bioinformatics research:</p><ul>
<li>
<p><strong>Community-Driven Projects</strong>: Collaborative platforms like GitHub will continue to foster innovation in tool development.</p>
</li>
<li>
<p><strong>Education and Training</strong>: Online courses and workshops will bridge skill gaps, enabling researchers from diverse backgrounds to contribute.</p>
</li>
</ul><h4>Challenges and Ethical Considerations</h4><p>While the future is bright, challenges remain. Data privacy and ethical concerns surrounding genetic information require careful navigation. Furthermore, addressing the digital divide is critical to ensuring equitable access to bioinformatics resources globally.</p><h4>Conclusion</h4><p>The future of bioinformatics is boundless, with opportunities to revolutionize our understanding of life and improve human health. As technologies evolve and collaborations flourish, bioinformatics will undoubtedly remain at the forefront of scientific discovery, unlocking the secrets of life one dataset at a time.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7815/post-doc-in-systems-genetics</guid>
  <pubDate>Wed, 08 Jan 2014 19:23:37 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post-doc in Systems Genetics]]></title>
  <description><![CDATA[
<p>Gagneur lab at Gene Center, Ludwig-Maximilians-Universitaet, Munich, Germany</p>

<p>Deadline for applications : January 15, 2014.</p>

<p>Description :</p>

<p>We seek a talented and motivated post-doc to develop computational methods for inferring the molecular basis of genetic diseases by integration of personal omics data. Research topics include: identifying causal mutations of rare disease patients by meta-analysis; inferring disease-causing molecular pathways from genotype, human phenotypes, and omics profile of patient-derived cell lines; and causal inference from longitudinal omics studies of patients. The developed methods will be applied to analyze data from our medical collaborators.</p>

<p>Candidates must either hold a PhD in computational biology or bioinformatics, or hold a PhD in physics, statistics, or applied mathematics with practical experience with high-dimensional data analysis. Experience in quantitative genetics is a plus. Applicants must have a proven publication record and an interest for translational research.</p>

<p>The Gagneur lab is a young, lively and multidisciplinary group with a research focus on systems genetics and gene regulation. It is located at the Gene Center of the LMU (University of Munich), an interdisciplinary institution whose 16 independent research groups investigate the regulation of gene expression at all levels - from the underlying molecular mechanisms to the biological system. The institute is located on the biomedical research campus Munich-Grosshadern, offering a dynamic, interactive and internationally oriented research environment. The dynamism of Munich and the proximity of the Alps provide an excellent quality of life.</p>

<p>The salary is according to the TV-L (German academic salary scale).<br />Applications including a cover letter, CV, and references must be sent by January 15th 2014 to Julien Gagneur (gagneur@genzentrum.lmu.de)</p>

<p>About the lab: http://www.gagneur.genzentrum.lmu.de</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44871/10-books-to-kickstart-and-level-up-your-bioinformatics-journey</guid>
	<pubDate>Tue, 12 Aug 2025 03:50:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44871/10-books-to-kickstart-and-level-up-your-bioinformatics-journey</link>
	<title><![CDATA[10 Books to Kickstart (and Level Up) Your Bioinformatics Journey]]></title>
	<description><![CDATA[<p>If you&rsquo;re starting out in bioinformatics or looking to sharpen your computational biology skills, having the right learning resources makes all the difference.<br />Here&rsquo;s my curated list of 10 must-read books &mdash; from beginner-friendly introductions to advanced computational genomics.</p><p>1️⃣ Data Analysis for the Life Sciences<br />A fantastic starting point to learn statistics, R programming, and exploratory data analysis in the context of biology. The best part? It&rsquo;s available free online from HarvardX.</p><p>2️⃣ Practical Computing for Biologists<br />The very first book I picked up when I started learning computational biology. It&rsquo;s beginner-friendly and focuses on essential computing skills every biologist needs.</p><p>3️⃣ A Primer for Computational Biology<br />An open-access, hands-on introduction to computational biology concepts and coding techniques. Perfect if you want to learn through real examples.</p><p>4️⃣ Computational Genomics with R<br />For those who already know R and want to dive deeper into genome-scale data analysis, from sequence alignment to gene expression.</p><p>5️⃣ The Biologist&rsquo;s Guide to Computing<br />Bridges the gap between biological problems and computational thinking, making it easier for life scientists to approach programming and data analysis.</p><p>6️⃣ Bioinformatics Data Skills<br />A must-read to sharpen your bioinformatics toolkit &mdash; from command-line skills to reproducible research workflows. Ideal once you&rsquo;ve covered the basics.</p><p>7️⃣ Bioinformatics Workbook<br />A practical tutorial series to help scientists design bioinformatics projects, analyze data, and understand best practices.</p><p>8️⃣ Modern Statistics for Modern Biology<br />An essential guide to modern statistical methods applied to biology, blending theory with hands-on examples in R.</p><p>9️⃣ Algorithms on Strings, Trees, and Sequences by Dan Gusfield<br />A classic reference for anyone wanting to understand the algorithms behind sequence alignment, genome assembly, and biological data structures.</p><p></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/7032/computer-experts-in-biotechnology-laboratory</guid>
	<pubDate>Wed, 04 Dec 2013 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/7032/computer-experts-in-biotechnology-laboratory</link>
	<title><![CDATA[Computer experts in biotechnology laboratory]]></title>
	<description><![CDATA[<p>Only bioinformatician can understand that <strong>multiplication</strong> and <strong>division</strong> are different but same thing :)</p><p><span>Disclaimer:</span>&nbsp;This cartoon is solely designed to create humour and fun, not to offend any computer experts.</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/7032" length="35726" type="image/gif" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/fun/view/45093/computational-but-a-biologist</guid>
	<pubDate>Thu, 09 Apr 2026 00:44:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/fun/view/45093/computational-but-a-biologist</link>
	<title><![CDATA[Computational, but a Biologist !]]></title>
	<description><![CDATA[<p>There was a time when doing biology<br />meant working only with your hands&mdash;<br />and that alone was seen<br />as &ldquo;real science.&rdquo;</p><p>People using computers were often seen<br />as helpers, not leaders&mdash;<br />useful, but not essential.</p><p>Sometimes, the criticism was direct.<br />Sometimes subtle.<br />But the message was the same&mdash;<br />this work doesn&rsquo;t really count.</p><p>Then biology changed.<br />The questions became bigger,<br />and experiments alone<br />were no longer enough.</p><p>Organizing knowledge by hand worked once.<br />Now it needs computers&mdash;<br />to handle scale, speed, and complexity.</p><p>Some patterns are simply invisible<br />if you look at one sample.<br />You need many&mdash;<br />and the right tools to understand them.</p><p>So we started building maps&mdash;<br />of genomes, cells, and systems.<br />Not perfect,<br />but extremely useful.</p><p>Ideas also had to become clearer.<br />It&rsquo;s no longer enough to say something sounds right&mdash;<br />you have to measure it.</p><p>The divide between &ldquo;types&rdquo; of biologists<br />never really made sense.<br />We are solving the same problems&mdash;<br />just in different ways.</p><p>Progress didn&rsquo;t wait for agreement.<br />It moved forward with data,<br />with code,<br />and with careful analysis.</p><p>What matters now is simple:<br />&bull; Biology depends on computation<br />&bull; Coding is an important skill<br />&bull; Statistics helps us think clearly<br />&bull; And the people building these tools<br />are shaping the future of science</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/6380/hidden-markov-models-viterbi-algorithm-markov-chain-exploration-with-script</guid>
	<pubDate>Thu, 14 Nov 2013 13:36:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/6380/hidden-markov-models-viterbi-algorithm-markov-chain-exploration-with-script</link>
	<title><![CDATA[Hidden Markov Models, Viterbi Algorithm, Markov Chain Exploration with script]]></title>
	<description><![CDATA[<p><strong>Hidden Markov Models, the Viterbi Algorithm, and CpG Islands (in VB6)</strong></p><p><strong>Problem :</strong></p><p>The CG island is a stretch of DNA (usually longer than 200 bases) in which the frequency of the CG sequence is higher than other regions. It is also called the CpG island, where "p" simply indicates that "C" and "G" are connected by a phosphodiester bond.<br /><br />CpG islands are often located around the promoters of housekeeping genes (which are essential for general cell functions) or other genes frequently expressed in a cell. At these locations, the CG sequence is not methylated. By contrast, the CG sequences in inactive genes are usually methylated to suppress their expression. The methylated cytosine may be converted to thymine by accidental deamination. Unlike the cytosine to uracil mutation which is efficiently repaired, the cytosine to thymine mutation can be corrected only by the mismatch repair which is very inefficient. Hence, over evolutionary time scales, the methylated CG sequence will be converted to the TG sequence.</p><p>Find step wise explanationand implementation steps at <a href="http://dna.cs.byu.edu/bio465/Labs/hmm.shtml">http://dna.cs.byu.edu/bio465/Labs/hmm.shtml</a></p><p>Source code with explanation <a href="http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/">http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/</a></p><p>Fore detail understanding of HMM read this excellent tutorial <a href="http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf">http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf</a></p><p>Viterbi Algo at <a href="http://en.wikipedia.org/wiki/Viterbi_path">http://en.wikipedia.org/wiki/Viterbi_path</a></p><p>For firther reading Wiki page <a href="http://en.wikipedia.org/wiki/Hidden_Markov_model">http://en.wikipedia.org/wiki/Hidden_Markov_model</a></p><p>On CpG island paper and for indepth understanding <a href="http://www.biomedcentral.com/1471-2164/12/S2/S10">http://www.biomedcentral.com/1471-2164/12/S2/S10</a></p><p>&nbsp;</p><p>If you are more interested in exploring&nbsp;Markov Chain Exploration and understand it with graphical version please visit <a href="http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1">http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1</a></p><p>Reference:</p><p>1.<a href="http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&amp;lngWId=1">http://www.planet-source-code.com</a></p><p>2. <a href="http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/">http://www.tannerhelland.com</a></p>]]></description>
	<dc:creator>Manisha Mishra</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>

</channel>
</rss>