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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28915?offset=260</link>
	<atom:link href="https://bioinformaticsonline.com/related/28915?offset=260" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43272/bioinformatics-head-bioinformatics-manager-iii-cancer-genomics-research-laboratory-at-frederick-national-laboratory</guid>
  <pubDate>Wed, 18 Aug 2021 00:19:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Head (Bioinformatics Manager III), Cancer Genomics Research Laboratory at  Frederick National Laboratory]]></title>
  <description><![CDATA[
<p>Frederick National Laboratory seeking an enthusiastic, creative, and seasoned bioinformatics professional to join our leadership team and direct the exceptional Bioinformatics Group at the Cancer Genomics Research Laboratory (CGR).  CGR has a diverse team of bioinformatics and computational scientists that support all areas of bioinformatics and data analysis (infrastructure, data QC, pipeline development and maintenance, data curation and sharing, methodology development, statistical analyses, machine learning approaches, and scientific interpretation).</p>

<p>More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&amp;c=leidosbiomed&amp;id=2040</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/859/boku-chair-of-bioinformatics</guid>
  <pubDate>Sun, 14 Jul 2013 12:37:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[Boku Chair of Bioinformatics]]></title>
  <description><![CDATA[
<p>The Bioinformatics group at Boku University has two main areas of interest, underpinning a common goal, the study of complex systems in living organisms. To overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes, novel views augmenting the classical gene by gene approaches are required. We combine<br />Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and<br />Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)</p>

<p>Link @ http://bioinf.boku.ac.at/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44703/the-role-of-lncrna-in-bioinformatics-unlocking-the-secrets-of-the-genome</guid>
	<pubDate>Sat, 07 Dec 2024 02:09:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44703/the-role-of-lncrna-in-bioinformatics-unlocking-the-secrets-of-the-genome</link>
	<title><![CDATA[The Role of lncRNA in Bioinformatics: Unlocking the Secrets of the Genome]]></title>
	<description><![CDATA[<p>In the intricate dance of molecular biology, long non-coding RNAs (lncRNAs) have emerged as key players, capturing the interest of researchers worldwide. These RNA molecules, once dismissed as "junk," have proven to be vital in the regulation of gene expression, cellular processes, and the progression of diseases. The intersection of lncRNA studies and bioinformatics is transforming our understanding of these enigmatic molecules, offering profound insights into their structure, function, and therapeutic potential.</p><h3>What Are lncRNAs?</h3><p>lncRNAs are RNA transcripts longer than 200 nucleotides that do not code for proteins. Despite their non-coding nature, they play diverse roles in gene regulation, including chromatin remodeling, transcriptional control, and post-transcriptional processing. Unlike messenger RNAs (mRNAs), lncRNAs often function as scaffolds, decoys, or guides in cellular machinery, influencing biological processes such as cell differentiation, immune response, and even cancer metastasis.</p><h3>Challenges in lncRNA Research</h3><p>Identifying and understanding lncRNAs pose unique challenges:</p><ol>
<li><strong>High Sequence Variability</strong>: Unlike protein-coding genes, lncRNAs exhibit low sequence conservation across species, making functional predictions difficult.</li>
<li><strong>Low Expression Levels</strong>: lncRNAs are often expressed at low levels, complicating their detection in transcriptomic data.</li>
<li><strong>Diverse Functions</strong>: The multifunctional nature of lncRNAs requires advanced computational tools to decipher their roles in complex networks.</li>
</ol><h3>Bioinformatics: A Crucial Ally in lncRNA Research</h3><p>Bioinformatics bridges the gap between raw biological data and meaningful insights, making it indispensable in lncRNA research. Here&rsquo;s how:</p><h4>1. <strong>Identification and Annotation</strong></h4><p>High-throughput sequencing technologies like RNA-seq generate vast amounts of data. Bioinformatics tools such as <em>StringTie</em>, <em>Cufflinks</em>, and <em>HISAT2</em> help assemble and annotate lncRNAs from this data. Additionally, databases like NONCODE, LNCipedia, and Ensembl provide curated repositories of lncRNA sequences and annotations.</p><h4>2. <strong>Functional Prediction</strong></h4><p>Bioinformatics algorithms predict the potential functions of lncRNAs by analyzing their interactions with DNA, RNA, and proteins. Tools like LncRNA2Function and RIblast utilize sequence motifs and secondary structure predictions to hypothesize about the roles of specific lncRNAs.</p><h4>3. <strong>Network Construction</strong></h4><p>lncRNAs often act as regulatory hubs. Bioinformatics platforms such as Cytoscape enable the visualization of lncRNA-mediated networks, elucidating their roles in pathways like cell cycle regulation and apoptosis.</p><h4>4. <strong>Epigenetic Studies</strong></h4><p>lncRNAs are known to interact with chromatin-modifying complexes, influencing gene expression epigenetically. Tools like ChIP-seq and ATAC-seq, combined with computational pipelines, identify these interactions and map them to the genome.</p><h4>5. <strong>Clinical Applications</strong></h4><p>Bioinformatics aids in the discovery of lncRNA biomarkers for diseases like cancer and neurodegenerative disorders. Machine learning models analyze differential expression profiles, helping prioritize lncRNAs with therapeutic potential.</p><h3>Case Study: lncRNAs in Cancer Research</h3><p>lncRNAs such as HOTAIR and MALAT1 have been implicated in cancer progression. Bioinformatics analyses have revealed their roles in promoting metastasis and altering the tumor microenvironment. For example, transcriptome analysis in cancer patients identifies lncRNA expression signatures, enabling precision medicine approaches.</p><h3>Future Directions</h3><p>The fusion of bioinformatics with experimental biology is unlocking the secrets of lncRNAs. Advances in artificial intelligence, single-cell sequencing, and structural modeling promise to overcome current limitations. Here are some promising directions:</p><ul>
<li><strong>Integrative Analysis</strong>: Combining multi-omics data to understand the interplay of lncRNAs with other biomolecules.</li>
<li><strong>CRISPR Screens</strong>: Leveraging bioinformatics to design CRISPR-based functional screens for lncRNAs.</li>
<li><strong>Therapeutic Development</strong>: Using bioinformatics to design lncRNA-based therapeutics, including antisense oligonucleotides and RNA interference tools.</li>
</ul><h3>Conclusion</h3><p>lncRNAs are the hidden gems of the genome, and bioinformatics is the key to unearthing their full potential. As research progresses, lncRNAs could pave the way for novel diagnostics, targeted therapies, and personalized medicine, revolutionizing our approach to complex diseases.</p><p>The journey into the world of lncRNAs is only beginning, and bioinformatics will continue to play a pivotal role in decoding these molecular mysteries. Whether you&rsquo;re a researcher, clinician, or bioinformatics enthusiast, the study of lncRNAs offers a fascinating frontier of discovery.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2042/ngs-course-medical-genomics-scheduled-for-17-20-september-2013-in-uz-leuven-belgium</guid>
	<pubDate>Mon, 12 Aug 2013 12:08:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2042/ngs-course-medical-genomics-scheduled-for-17-20-september-2013-in-uz-leuven-belgium</link>
	<title><![CDATA[NGS course Medical Genomics, scheduled for 17-20 September 2013 in UZ Leuven (Belgium).]]></title>
	<description><![CDATA[<p>This course is open to all students and postdocs and registration for all academic participants is free of charge. To help us in organizing the course, please register online via http://gc.uzleuven.be where the preliminary program is also available.</p><p>This course is organized with support from the IAP &ldquo;Belgian Medical Genomics Initiative&rdquo;, SymBioSys and the Genomics Core.</p><p>For inquiries, please email Ms Narcisse Opdekamp ( narcisse.opdekamp@uzleuven.be ).</p><p>More at &gt;&gt;&nbsp;<a href="http://gc.uzleuven.be/">http://gc.uzleuven.be/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6458/bigre-lab</guid>
  <pubDate>Sun, 17 Nov 2013 10:35:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[BIGRE Lab]]></title>
  <description><![CDATA[
<p>The Laboratoire de Bioinformatique des Génomes et des Réseaux (Genome and Network Bioinformatics) is specialized in the conception, implementation, evaluation and application of bioinformatics approaches for the analysis of genome, transcriptome, proteome and metabolism.<br />Our main activities include</p>

<p>Analysis of regulatory sequences (RSAT project)<br />Classification and analysis of mobile genetic elements (ACLAME project).<br />Analysis of molecular interaction networks (NeAT project)<br />Inference of metabolic pathways from genomic and post-genomic data <br />(metabolic pathfinding, see also metabolic pathfinding in NeAT)<br />Critical assesment of protein interactions (CAPRI)</p>

<p>Lab Page http://www.bigre.ulb.ac.be/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata</guid>
	<pubDate>Tue, 11 Jun 2019 21:27:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata</link>
	<title><![CDATA[Amity University Bioinformatics Summer Program - Kolkata]]></title>
	<description><![CDATA[<p>Registrations are now open for the 2019 Summer Bioinformatics Training program at Amity University, Kolkata. The program will focus on introductory topics for life science students. We will review important history, topics and challenges bioinformatics can help address in the context of basic research, discovery and industry.</p><p>Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/</p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6961/research-assistant-national-bureau-of-animal-genetic-resources</guid>
  <pubDate>Tue, 03 Dec 2013 06:17:34 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Assistant @ NATIONAL BUREAU OF ANIMAL GENETIC RESOURCES]]></title>
  <description><![CDATA[
<p>NATIONAL BUREAU OF ANIMAL GENETIC RESOURCES<br />Near Basant Vihar G.T. Road Bypass<br />P.O. Box No.129, Karnal-132001 (Haryana)</p>

<p>WALK-IN-INTERVIEW</p>

<p>A walk-in-Interview is proposed to be held at National Bureau of Animal Genetic Resources, Karnal (Haryana)-132001 at 11:30 AM on 18.12.2013 to select One RA and One SRF as per details given below:</p>

<p>1. One post of Research Associate under DBT sponsored Support under BIPP for the “SanGenix: A comprehensive Next Generation Sequence (NGS) data analysis solution” as Grants in AID. Thepost duration is Upto 31st March 2015 or earlier.</p>

<p>2. One post of Senior Research Fellow under NAIP (Component-4) Bioprospecting of genes and allele mining for abiotic stress tolerance. The post duration is Upto 31st March 2014 or earlier</p>

<p>Essential Qualifications: Ph.D. in Bioinformatics/ Computer Application or<br />First Class Masters degree in Bioinformatics/ Computer Application with two years experience as evidenced by Publications.</p>

<p>Desirable: Experience in the field of handling Next generation Sequencing Data.</p>

<p>Emolument: Rs. 22,000/- per month + HRA as per admissibility</p>

<p>Age Limit:</p>

<p>40 years for Men<br />45 years for women as on date of interview</p>

<p>Research Associate: ONE</p>

<p>Duration of engagement: Upto</p>

<p>31st March 2015 or earlier &amp; Coterminus with the project</p>

<p>Responsibilities: To help the PI for Beta testing and development of the SanGenix Tool for NGS data.</p>

<p>Essential Qualifications: First Class Masters’ degree in Bioinformatics/Biotechnology.</p>

<p>Desirable: Experience in the field of Biotechnology/ Bioinformatics</p>

<p>Emoluments:</p>

<p>Rs. 16,000/- per month + HRA as per admissibility.<br />Senior Research Fellow: ONE<br />Duration of engagement: Upto 31st March 2014 or earlier &amp; Coterminus with the project</p>

<p>Age Limit</p>

<p>35 years for men<br />40 years for women as on date of interview</p>

<p>Note: Relaxation in age will be admissible for SC/ST &amp; OBC candidates as per Govt. of India /ICAR norms</p>

<p>1. The applicants must bring with them original documents and brief of research work done during post graduation along with a set of photocopy and latest two passport size photographs.<br />2. A panel of selected candidates will also be made which may be utilized for filling of positions of shorter durations in future if demand arises.<br />3. Experience certificate in original, if any 4. The above positions are purely on temporary basis and are co-terminus with the project. No TA/DA will be paid to attend the interview.<br />5. Any other clarifications can be had on the date of interview.<br />6. The Director’s decision will be final and binding on all respects.</p>

<p>Advertisement: http://210.212.93.85/rasrfadvertise.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44770/nvidia-and-arc-institute-unveil-evo-2-a-breakthrough-ai-for-dna-design</guid>
	<pubDate>Fri, 21 Feb 2025 10:39:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44770/nvidia-and-arc-institute-unveil-evo-2-a-breakthrough-ai-for-dna-design</link>
	<title><![CDATA[NVIDIA and Arc Institute Unveil Evo 2: A Breakthrough AI for DNA Design]]></title>
	<description><![CDATA[<p>NVIDIA and the Arc Institute have introduced <strong style="font-size: 12.8px;">Evo 2</strong>, a groundbreaking AI model designed to <strong style="font-size: 12.8px;">understand, predict, and generate DNA sequences</strong>. This marks a major advancement in computational biology, offering scientists an unprecedented tool to decode the genetic blueprint of life and even design entirely new biological systems.</p><h3><strong>The Power of Evo 2: AI Meets DNA</strong></h3><p>Evo 2 is <strong>the largest AI model for biology ever created</strong>, trained on an astonishing <strong>9.3 trillion DNA "letters"</strong> (nucleotides) carefully selected from genomes spanning the entire tree of life. This massive dataset ensures that Evo 2 can recognize patterns and relationships in genetic sequences at an unparalleled scale.</p><p>For the first time, scientists can <strong>design DNA with AI</strong>, moving beyond simple sequence analysis to active DNA generation. Evo 2 enables researchers to <strong>predict, modify, and even create entire genetic sequences</strong>, opening new possibilities in medicine, agriculture, and synthetic biology.</p><h3><strong>Decoding the Dark Genome</strong></h3><p>One of the biggest challenges in genetics is understanding the <strong>non-coding regions</strong> of DNA&mdash;vast stretches of the genome that do not code for proteins but play crucial roles in regulating gene expression. These regions control when and how genes are activated, influencing everything from development to disease.</p><p>Evo 2 is designed to <strong>decode these non-coding elements</strong>, helping researchers uncover their functions and use this knowledge to develop gene-based therapies, synthetic life forms, and precision agriculture solutions.</p><h3><strong>From Reading DNA to Writing It</strong></h3><p>To put Evo 2&rsquo;s impact into perspective:</p><ul>
<li><strong>Previous AI models could "read" DNA</strong> like a book, analyzing genetic sequences and identifying patterns.</li>
<li><strong>Evo 2 can "write" entirely new DNA</strong>, designing functional genes, chromosomes, and even full genomes from scratch.</li>
</ul><p>This means scientists can now <strong>engineer biological systems with AI</strong>, designing new proteins, metabolic pathways, and genetic circuits to address real-world challenges.</p><h3><strong>A Step Toward Generative Biology</strong></h3><p>The Arc Institute describes Evo 2 as a major step toward <strong>"generative biology"</strong>&mdash;a revolutionary approach where AI is used to create <strong>novel biological structures</strong> rather than just analyzing existing ones. This could lead to breakthroughs such as:</p><ul>
<li><strong>New medicines</strong>: AI-generated enzymes and proteins tailored for targeted therapies.</li>
<li><strong>Disease-resistant crops</strong>: Genetically optimized plants for higher yield and climate resilience.</li>
<li><strong>Synthetic organisms</strong>: Custom-designed microbes for bioremediation, biofuel production, and industrial applications.</li>
</ul><h3><strong>An Open-Source Revolution</strong></h3><p>Unlike many proprietary AI models, <strong>Evo 2 is open source</strong>, making its capabilities accessible to researchers worldwide. This democratization of AI-driven biology means that scientists from different disciplines can <strong>collaborate, experiment, and innovate</strong>, accelerating discoveries in genetic engineering and synthetic biology.</p><p>With Evo 2, the boundaries of what&rsquo;s possible in <strong>DNA design, genetic engineering, and biological innovation</strong> are being redrawn. The future of life sciences is no longer just about understanding life&rsquo;s code&mdash;it&rsquo;s about writing it.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/7986/list-of-bioinformatics-open-source-projectssoftware</guid>
	<pubDate>Tue, 21 Jan 2014 14:28:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/7986/list-of-bioinformatics-open-source-projectssoftware</link>
	<title><![CDATA[List of bioinformatics open source projects/software.]]></title>
	<description><![CDATA[<p>Open source software is software that can be freely used, changed, and shared (in modified or unmodified form) by anyone. Open source software is made by many people, and distributed under licenses that comply with the Open Source Definition.The Open Source Initiative (OSI) is a global non-profit that supports and promotes the open source movement. Followings are the OS bioinformatics projects/software :</p><p><strong>.NET Bio</strong></p><p>http://blogs.msdn.com/b/msr_er/archive/2011/10/18/microsoft-biology-foundation-evolves-into-new-toolkit-net-bio.aspx</p><p>A language-neutral bioinformatics toolkit built using the Microsoft 4.0 .NET Framework to help developers, researchers, and scientists.</p><p><strong>AMPHORA</strong> ("AutoMated Phylogenomic infeRence Application")</p><p>http://wolbachia.biology.virginia.edu/WuLab/Software.html</p><p><a href="http://en.wikipedia.org/wiki/Metagenomics" title="Metagenomics">Metagenomics</a> analysis software</p><p><strong>Anduril</strong></p><p>http://www.anduril.org/anduril/site/</p><p>Component-based <a href="http://en.wikipedia.org/wiki/Workflow" title="Workflow">workflow</a> framework for data analysis</p><p>Armadillo workflow platform</p><p>Tool for designing and executing phylogenetic workflows</p><p><strong>AutoDock</strong></p><p>http://autodock.scripps.edu/</p><p>suite of automated docking tools</p><p><strong>Biochemical Algorithms Library (BALL)</strong></p><p>http://www.ball-project.org/</p><p>C++ library and framework for molecular modeling and visualization designed for rapid prototyping</p><p><strong>Bio4j</strong></p><p>http://bio4j.com/</p><p>Bio4j is a <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a> platform and <a href="http://en.wikipedia.org/wiki/Chart" title="Chart">graph</a> based <a href="http://en.wikipedia.org/wiki/Database" title="Database">database</a> built around most data available in <a href="http://en.wikipedia.org/wiki/UniProt" title="UniProt">UniProt</a> KB(<a href="http://en.wikipedia.org/wiki/Swiss-Prot" title="Swiss-Prot">Swiss-Prot</a> + <a href="http://en.wikipedia.org/wiki/TrEMBL" title="TrEMBL">TrEMBL</a>), <a href="http://en.wikipedia.org/wiki/Gene_Ontology" title="Gene Ontology">Gene Ontology</a> (GO), <a href="http://en.wikipedia.org/w/index.php?title=UniRef&amp;action=edit&amp;redlink=1" title="UniRef (page does not exist)">UniRef</a> (50,90,100), <a href="http://en.wikipedia.org/wiki/RefSeq" title="RefSeq">RefSeq</a>, <a href="http://en.wikipedia.org/wiki/National_Center_for_Biotechnology_Information" title="National Center for Biotechnology Information">NCBI</a> taxonomy, and Expasy Enzyme DB</p><p><strong>Bioclipse</strong></p><p>www.bioclipse.net</p><p>Visual platform for <a href="http://en.wikipedia.org/wiki/Cheminformatics" title="Cheminformatics">chemo</a>- and <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a> based on the <a href="http://en.wikipedia.org/wiki/Eclipse_%28software%29" title="Eclipse (software)">Eclipse</a> Rich Client Platform (RCP).</p><p><strong>Bioconductor</strong></p><p>http://www.bioconductor.org/</p><p><a href="http://en.wikipedia.org/wiki/R_%28programming_language%29" title="R (programming language)">R (programming language)</a> language toolkit</p><p><strong>Bioinformatics Learning Tutorial (BLT)</strong></p><p>http://sourceforge.net/projects/biotutorial/</p><p>Educational <a href="http://en.wikipedia.org/wiki/Interactive_tutorials" title="Interactive tutorials">interactive tutorials</a> and 3D animations for Replication, Transcription, and Translation</p><p><strong>BioHaskell</strong></p><p>http://biohaskell.org/</p><p><a href="http://en.wikipedia.org/wiki/Haskell_%28programming_language%29" title="Haskell (programming language)">Haskell (programming language)</a></p><p><strong>BioJava</strong></p><p>http://biojava.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Java_%28programming_language%29" title="Java (programming language)">Java (programming language)</a></p><p><strong>BioMOBY</strong></p><p>http://biomoby.org/</p><p>registry of <a href="http://en.wikipedia.org/wiki/Web_services" title="Web services">web services</a></p><p><strong>BioPerl</strong></p><p>http://www.bioperl.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Perl" title="Perl">Perl</a> language toolkit</p><p><strong>BioPHP</strong></p><p>http://www.biophp.org/</p><p><a href="http://en.wikipedia.org/wiki/PHP" title="PHP">PHP</a> language toolkit</p><p><strong>Biopython</strong></p><p>http://biopython.org/wiki/Main_Page</p><p><a href="http://en.wikipedia.org/wiki/Python_%28programming_language%29" title="Python (programming language)">Python</a> language toolkit</p><p><strong>BioRails</strong></p><p>https://github.com/biorails</p><p>a <a href="http://en.wikipedia.org/wiki/Data_management_system" title="Data management system">data management system</a> designed to support researchers in <a href="http://en.wikipedia.org/wiki/Drug_discovery" title="Drug discovery">drug discovery</a></p><p><strong>BioRuby</strong></p><p>http://bioruby.org/</p><p><a href="http://en.wikipedia.org/wiki/Ruby_%28programming_language%29" title="Ruby (programming language)">Ruby</a> language toolkit</p><p><strong>BioSmalltalk</strong></p><p>https://code.google.com/p/biosmalltalk/</p><p><a href="http://en.wikipedia.org/wiki/Smalltalk_%28programming_language%29" title="Smalltalk (programming language)">Smalltalk</a> language toolkit</p><p><strong>BioUno</strong></p><p>http://www.biouno.org/</p><p><a href="http://en.wikipedia.org/w/index.php?title=BioUno&amp;action=edit&amp;redlink=1" title="BioUno (page does not exist)">BioUno</a> is a project that applies <a href="http://en.wikipedia.org/wiki/Continuous_Integration" title="Continuous Integration">Continuous Integration</a> tools and techniques in <a href="http://en.wikipedia.org/wiki/Bioinformatics" title="Bioinformatics">Bioinformatics</a>. It uses <a href="http://en.wikipedia.org/wiki/Jenkins_%28software%29" title="Jenkins (software)">Jenkins</a> and its plug-in API to create <a href="http://en.wikipedia.org/wiki/Bioinformatics_workflow_management_system" title="Bioinformatics workflow management system">biology workflows</a> and manage <a href="http://en.wikipedia.org/wiki/Computer_clusters" title="Computer clusters">computer clusters</a>.</p><p><strong>caCORE</strong></p><p>&nbsp;</p><p>ontologic representation environment</p><p><strong>caArray</strong></p><p>https://cabig-stage.nci.nih.gov/community/tools/caArray</p><p>ontologic representation environment</p><p><strong>EMBOSS</strong></p><p>http://emboss.sourceforge.net/</p><p>Suite of packages for sequencing, searching, etc.</p><p><strong>Gaggle</strong></p><p>https://www.gaggle.net/</p><p>A framework for interoperability between systems biology software</p><p><strong>Galaxy</strong></p><p>http://galaxyproject.org/</p><p><a href="http://en.wikipedia.org/wiki/Scientific_workflow_system" title="Scientific workflow system">Scientific workflow</a> and <a href="http://en.wikipedia.org/wiki/Data_integration" title="Data integration">data integration</a> system</p><p><strong>GenePattern</strong></p><p>http://www.broadinstitute.org/cancer/software/genepattern/</p><p><a href="http://en.wikipedia.org/wiki/Scientific_workflow_system" title="Scientific workflow system">Scientific workflow system</a> that provides access to more than 150 genomic analysis tools</p><p><strong>GeWorkbench</strong></p><p>http://wiki.c2b2.columbia.edu/workbench/index.php/Home</p><p>Genomic <a href="http://en.wikipedia.org/wiki/Data_integration" title="Data integration">data integration</a> platform</p><p><strong>GMOD</strong></p><p>http://www.gmod.org/wiki/Main_Page</p><p>Toolkit for addressing many common challenges at biological databases.</p><p><strong>GeneProf</strong></p><p>http://www.geneprof.org/GeneProf/</p><p>A web-based, bioinformatics software suite for the analysis of functional genomics experiments, e.g. RNA-seq or ChIP-seq.</p><p><strong>GeneTalk</strong></p><p>http://www.gene-talk.de/</p><p>Tool for filtering sequence variants in <a href="http://en.wikipedia.org/wiki/Variant_Call_Format" title="Variant Call Format">VCF</a> files. Network for scientists and clinicians for expertise and knowledge exchange. Database of annotations aboute sequence variants with clinically relevant information.</p><p><strong>GenGIS</strong></p><p>http://kiwi.cs.dal.ca/GenGIS/Main_Page</p><p>Application that allows users to combine digital map data with information about biological sequences collected from the environment.</p><p><strong>GenomeSpace</strong></p><p>http://www.genomespace.org/</p><p>Centralized web application that provides data format transformations and facilitates connections with other bioinformatics tools</p><p><strong>GENtle</strong></p><p>http://directory.fsf.org/wiki/GENtle</p><p>An equivalent to the proprietary <a href="http://en.wikipedia.org/wiki/Vector_NTI" title="Vector NTI">Vector NTI</a>, a tool to analyze and edit <a href="http://en.wikipedia.org/wiki/DNA" title="DNA">DNA</a> sequence files</p><p><strong>Integrated Genome Browser</strong></p><p>http://bioviz.org/igb/</p><p><a href="http://en.wikipedia.org/wiki/Java_%28software_platform%29" title="Java (software platform)">Java</a>-based desktop <a href="http://en.wikipedia.org/wiki/Genome_browser" title="Genome browser">genome browser</a></p><p><strong>Integrative Genomics Viewer (IGV)</strong></p><p>http://www.broadinstitute.org/igv/</p><p>High-performance desktop tool for interactive visual exploration of diverse genomic data</p><p><strong>IntAct</strong></p><p>http://www.ebi.ac.uk/intact/</p><p>molecular interaction database</p><p><strong>InterMine</strong></p><p>http://intermine.github.io/intermine.org/</p><p>Extensive data warehouse system for the analysis and integration of biological datasets</p><p><strong>Java Treeview</strong></p><p>http://jtreeview.sourceforge.net/</p><p>microarray data viewer</p><p><strong>LabKey Server</strong></p><p>http://labkey.com/</p><p>platform for integrating, analyzing and sharing data</p><p><strong>OpenClinica</strong></p><p>https://www.openclinica.com/</p><p>software for capturing and managing data in clinical trials</p><p><a href="http://www.biomedcentral.com/1471-2164/13/512">PromKappa</a></p><p>http://xbioinformatics.wordpress.com/tag/promkappa/</p><p>PromKappa (Promoter analysis by Kappa) software program used for promoter pattern generation and promoter analysis.</p><p><strong>MeV: Multi-Experiment Viewer</strong></p><p>http://www.tm4.org/mev.html</p><p>a desktop application for the analysis, visualization and data-mining of large-scale genomic data</p><p><strong>PathVisio</strong></p><p>http://www.pathvisio.org/</p><p>a desktop software for drawing, analysis and visualization of biological pathways</p><p>REDCRAFT</p><p>software for determining tertiary protein structure given assigned Residual Dipolar Coupling data</p><p>SAM Tools</p><p>Data format (SAM) and accompanying tool suite, for storing large nucleotide sequence alignments</p><p><a href="http://en.wikipedia.org/wiki/Staden_Package" title="Staden Package">Staden Package</a></p><p>Sequence assembly, editing and analysis, primarily consisting of gap4, gap5 and spin.</p><p><a href="http://en.wikipedia.org/wiki/STAMP" title="STAMP">STAMP</a></p><p>Software package for analyzing metagenomic profiles that promotes &lsquo;best practices&rsquo; in choosing appropriate statistical techniques and reporting results.</p><p><a href="http://supfam.org/supraHex">supraHex</a></p><p>An open-source R/Bioconductor package for omics data analysis using a supra-hexagonal map</p><p><a href="http://en.wikipedia.org/wiki/Taverna_workbench" title="Taverna workbench">Taverna workbench</a></p><p>Tool for designing and executing workflows</p><p>TGAC Browser</p><p>Genome Browser, visualisation solutions for big data in the genomic era</p><p>T-REX WebServer</p><p>Bioinformatics and phylogenetics webserver (NJ, PhyML, RAxML, MAFFT, MUSCLE, Newick viewer, <a href="http://en.wikipedia.org/wiki/Horizontal_gene_transfer" title="Horizontal gene transfer">Horizontal gene transfer</a> detection, Reticulograms, Substitution models)</p><p><a href="http://en.wikipedia.org/wiki/UGENE" title="UGENE">UGENE</a></p><p>integrated bioinformatics tools</p><p>Visomics</p><p>bioinformatics tools for omics data</p><p>Genome Analysis Toolkit 1.0 (GATK 1.0)</p><p>a software package to analyse next-generation resequencing data</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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