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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30355?offset=590</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5661/shankar-lab</guid>
  <pubDate>Wed, 16 Oct 2013 07:02:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Shankar Lab]]></title>
  <description><![CDATA[
<p>Research Interest:</p>

<p>(A) Regulatory System Analysis with respect to microRNAs</p>

<p>(B) Computational Epigenomics &amp; Regulomics:</p>

<p>(C) Computational issues with Next Generation Sequencing:</p>

<p>Department of Biotechnology, <br />Institute of Himalyan Bioresources Technology<br />CSIR, Palampur(Himachal Pradesh), India.<br />Email: ravishihbt.res.in; ravish9gmail.com</p>

<p>More @ http://scbb.ihbt.res.in/SCBB_dept/Lab_Member.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43439/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite</guid>
	<pubDate>Wed, 06 Oct 2021 07:01:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43439/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite</link>
	<title><![CDATA[MMseqs2: ultra fast and sensitive sequence search and clustering suite]]></title>
	<description><![CDATA[<p><span>MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.</span></p><p>Address of the bookmark: <a href="https://github.com/soedinglab/MMseqs2" rel="nofollow">https://github.com/soedinglab/MMseqs2</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5747/dbbrowser-attwood-lab</guid>
  <pubDate>Fri, 18 Oct 2013 10:48:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[DbBrowser: Attwood Lab]]></title>
  <description><![CDATA[
<p>DbBrowser: Attwood Lab research concerns protein sequence analysis, primarily using the method of protein 'fingerprinting'. DbBrowser: Attwood Lab maintain a diagnostic fingerprint database (PRINTS), one of the founding partner of InterPro. We also design software to display sequence and structural data in visually-striking ways (e.g., Ambrosia, CINEMA); DbBrowser: Attwood Lab are building re-usable software components to create semantically integrated bioinformatics applications through UTOPIA, including a 'smart' PDF reader that links bioinformatics databases and tools directly with scientific articles (Utopia Documents); and have developed a number of tools for automatic annotation and text mining (e.g., MINOTAUR, PRECIS, METIS). </p>

<p>More @ http://www.bioinf.manchester.ac.uk/dbbrowser/index.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</guid>
	<pubDate>Fri, 06 Apr 2018 12:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</link>
	<title><![CDATA[d3Network:Tools for creating D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.]]></title>
	<description><![CDATA[<p><a href="http://bost.ocks.org/mike/">Mike Bostock</a><span>&rsquo;s&nbsp;</span><a href="http://d3js.org/">D3.js</a><span>&nbsp;is great for creating&nbsp;</span><a href="http://bl.ocks.org/mbostock/4062045">interactive network graphs</a><span>&nbsp;with JavaScript. The&nbsp;</span><a href="https://github.com/christophergandrud/d3Network">d3Network</a><span>&nbsp;package makes it easy to create these network graphs from&nbsp;</span><a href="http://www.r-project.org/">R</a><span>. The main idea is that you should able to take an R data frame with information about the relationships between members of a network and create full network graphs with one command.</span></p><p>Address of the bookmark: <a href="http://christophergandrud.github.io/d3Network/" rel="nofollow">http://christophergandrud.github.io/d3Network/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5946/bioinformatics-tata-memorial-centre-navi-mumbai</guid>
  <pubDate>Mon, 28 Oct 2013 10:40:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics @ TATA MEMORIAL CENTRE, NAVI MUMBAI]]></title>
  <description><![CDATA[
<p>TATA MEMORIAL CENTRE<br />ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER<br />KHARGHAR, NAVI MUMBAI – 410210</p>

<p>No. ACTREC/Advt./ 72 /2013</p>

<p>WALK IN INTERVIEW</p>

<p>1. JRF*<br />Genome-wide RNAi screen with human pooled tyrosine kinase shRNA libraries in head and neck squamous call carcinoma (HNSCC) cell lines<br />DBT A/C No. 3071, Dr. Amit Dutt</p>

<p>2. JRF<br />IRB Project ACTREC Funds<br />Dr. Amit Dutt</p>

<p>3. RA<br />Defining the cancer genome of Head and Neck Squamous Cell Carcinoma (HNSCC) with SNP arrays and next generation sequencing technology<br />A/C No. 2895, Dr. Amit Dutt</p>

<p>Duration of the Project: One year from the date of appointment, or as and when project terminates.</p>

<p>Consolidated Salary: RA : Rs. 40,000/- p.m.<br />JRF* (DBT): Rs. 20,800/- p.m.<br />JRF: Rs. 16,000/- p.m.<br />Date &amp; Time: 6th November, 2013, at 10.00 a.m.</p>

<p>Venue: Conference Room</p>

<p>Minimum Qualifications and Experience:</p>

<p>RA: The ideal applicant should have a PhD in a relevant field. He/she should have a strong computational biology background, with demonstrated experience in coding using Perl, Python, Java or C++. He/she should be familiar with working in unix enviromnent, devising computational algorithms for data analysis, statistical data analysis in R and matlab and database programming using MySQL. Hands on experience in analyzing high throughput data would be an added advantage.</p>

<p>JRF* (DBT project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Valid UGC-CSIR/DBT/ICMR JRF qualification and laboratory experience in molecular biology. Previous experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team would be desirable.</p>

<p>JRF (ACTREC project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Minimum 2 yrs experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team is essential.</p>

<p>*M.Sc. degree obtained after a one year course will not be considered.</p>

<p>Candidates fulfilling above requirements should send their application by e-mail to<br />‘careers.duttlab@gmail.com. in the format given below so as to reach on or before<br />4th November, 2013.</p>

<p>Advertisement:</p>

<p>http://www.actrec.gov.in/data%20files/2013/AD-RA-JR-TECHN-6-NOV.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36398/tools-for-protein-protein-docking</guid>
	<pubDate>Wed, 25 Apr 2018 05:15:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36398/tools-for-protein-protein-docking</link>
	<title><![CDATA[Tools for Protein-Protein Docking !]]></title>
	<description><![CDATA[<p>Predicting the structure of protein&ndash;protein complexes using docking approaches is a difficult problem whose major challenges include identifying correct solutions, and properly dealing with molecular flexibility and conformational changes. Following are the tools to predict&nbsp;<span>the structure of protein&ndash;protein complexes:</span></p><p><a href="http://www.sbg.bio.ic.ac.uk/docking/index.html" target="_blank">3D-Dock Suite</a></p><p>Global rigid search: FFTShape complementarity and electrostatics</p><p>Re-scoring and clustering. Refinement of interface side-chains</p><p><a href="http://www.sbg.bio.ic.ac.uk/~3dgarden/" target="_blank">3D-Garden</a></p><p>Global rigid search in ensamble</p><p>Shape complementarity and Lennard&ndash;Jones potential</p><p>Side chain and backbone dihedral refinement</p><p><a href="http://www.sdsc.edu/CCMS/DOT/" target="_blank">DOT</a></p><p>Global rigid search: FFTShape complementarity, electrostatics and VDWNone</p><p><a href="http://users.unimi.it/~ddl/escherng/index.htm" target="_blank">Escher NG</a></p><p>Global rigid searchShape complementarity, hydrogen bonds and electrostatic</p><p>Integrated in&nbsp;<a href="http://users.unimi.it/~ddl/vega/download.htm" target="_blank">VEGA</a></p><p><a href="http://vakser.bioinformatics.ku.edu/resources/gramm/gramm1" target="_blank">GRAMM</a>&nbsp;</p><p>Global rigid search: FFT. smooth protein surface representation for soft docking</p><p>Shape complementarity and Lennard-Jones potential</p><p>Clustering of conformations</p><p><a href="http://vakser.bioinformatics.ku.edu/resources/gramm/grammx/" target="_blank">GRAMM-X</a>&nbsp;</p><p>Global rigid search: FFT. smooth protein surface representation for soft docking</p><p>Shape complementarity and Lennard-Jones potentialminimization and re-scoring with multiple filters</p><p><a href="http://www.loria.fr/~ritchied/hex_server/" target="_blank">HEX</a></p><p>Global rigid search: Fourier correlation of spherical harmonics</p><p>Shape complementarity</p><p><a href="http://www.csd.abdn.ac.uk/hex/" target="_blank"></a><a href="http://haddock.chem.uu.nl/Haddock/haddock.php" target="_blank">HADDOCK</a></p><p>Global rigid searchElectrostatic ,VDW and desolvation energy termsMD simulated annealing refinement . Filtering based on external data.&nbsp;</p><p><a href="http://www.molsoft.com/docking.html">ICM</a></p><p>Global rigid search: Monte CarloEmpirical scoring function</p><p>Clustering and selection of conformations. Refinement of interface side-chains and re-scoring</p><p><a href="http://www.weizmann.ac.il/Chemical_Research_Support/molfit/" target="_blank">MolFit&nbsp;</a></p><p>Global rigid search: FFTShape complementarity</p><p>Clustering of good solutions, filtering using&nbsp;<em>a priori&nbsp;</em>information and small, local rigid rotations around selected conformations</p><p><a href="http://bioinfo3d.cs.tau.ac.il/PatchDock/" target="_blank">PatchDock</a></p><p>Global rigid searchShape complementarity and atomic desolvation energy</p><p>Clustering of conformations</p><p><a href="http://inb.bsc.es/gn6/PyDock" target="_blank">PyDock</a></p><p>Global rigid search:FFTShape complementarity</p><p>rescoring by binding electrostatics and desolvation energy</p><p><a href="http://bioinfo3d.cs.tau.ac.il/PatchDock/" target="_blank"></a><a href="http://rosettadock.graylab.jhu.edu/" target="_blank">RosettaDock</a></p><p>Local rigid search: Monte Carlo with low and high resolution structure representation levels</p><p>Different scoring parameters for the different resolutions&nbsp;</p><p><a href="http://zlab.bu.edu/zdock/" target="_blank">ZDOCK</a></p><p>Global rigid search: FFTShape complementarity, desolvation energy, and electrostatics.</p><p>Energy minimization and re-scoringFree for academics</p><p>&nbsp;</p><p>Point to note:</p><p>The proper treatment of flexibility in protein&ndash;protein docking is still an active field of research. You first should analyzed your proteins in order to define their conformational space and then choose the most suitable method for your docking problem.</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6012/project-junior-research-fellow-ccmb</guid>
  <pubDate>Fri, 01 Nov 2013 10:38:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Junior Research Fellow @ CCMB]]></title>
  <description><![CDATA[
<p>Temporary Project positions available purely on temporary basis - Oct/2013</p>

<p>1. Project Junior Research Fellow / Project Assistant</p>

<p>Last Date: 11th Nov 2013</p>

<p>Qualification B.Tech (Comp. Sci.), B.Tech/M.Tech (Bioinformatics), MCA,  M.Sc. (Mathematics/Statistics)</p>

<p>Desirable Qualifications: Programming in FORTRAN/ C /PERL, Web application technologies</p>

<p>Upper Age limit 28</p>

<p>Rs.12000 / Rs.16000 (as sanctioned by the funding agency)</p>

<p>General terms and conditions:</p>

<p>    Positions are purely temporary and co-terminus with the project.</p>

<p>    HRDG (CSIR) prevailing guidelines are applicable these positions.</p>

<p>    All categories of applicants are required to submit online application.</p>

<p>    Enhancement of stipend to Project JRF to Project SRF will be with the due recommendation of Principal Investigator and approval of the Director on the evaluation of the 3 member Standing Committee consisting of Chairperson at the level of Chief Scientist, Coordinator of the JRFs/RAs/PDFs and the Principal Investigator of the Project.</p>

<p>    The age relaxation as per HRDG (CSIR) norms: SC/ST/OBC/Women/Physically Handicapped persons – five years.</p>

<p>    The Stipend normally be fixed at Rs.22000/- for Research Associates/Post Doc. Fellows. However, a selected RA/PDF may be placed in the higher start of stipend if there is ample justification and such recommendation is made by the Selection Committee. Based on the recommendation with justification by the PI and approval of the Director, person getting stipend at lower rate may be elevated to higher rate subject to availability of the funds in the project.</p>

<p>    Recruitment will be based on initial screening based on qualifications and experience criteria and also based on suitability of the candidates to the nature of research project. This screening will be followed by written test followed / interview. After completing this process, candidates will be shortlisted and appointed in specific project subjects as and when appropriate positions become available. The pool of selected candidates will be valid for six months.</p>

<p>    Remunerations indicate are maximum admissible and will depend upon the availability of funds and subject to conditions applicable to projects from different funding agencies at the time of recruitment.</p>

<p>Apply : http://www.ccmb.res.in/positions/projects/temp_positions.php</p>

<p>Form download : http://www.ccmb.res.in/positions/projects/oct-2013/pdf_download.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Tue, 08 May 2018 04:39:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see</span><br><a href="http://arthropods.eugenes.org/EvidentialGene/" target="_blank">http://arthropods.eugenes.org/EvidentialGene/<span></span></a><br><br><span>Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. See project wiki/blog for notes.</span></p>
<p><span>Download&nbsp;</span></p>
<p>http://arthropods.eugenes.org/EvidentialGene/trassembly.html</p>
<p>https://sourceforge.net/p/evidentialgene/blog/</p><p>Address of the bookmark: <a href="http://arthropods.eugenes.org/EvidentialGene/trassembly.html" rel="nofollow">http://arthropods.eugenes.org/EvidentialGene/trassembly.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6233/edwards-lab</guid>
  <pubDate>Sun, 10 Nov 2013 15:07:08 -0600</pubDate>
  <link></link>
  <title><![CDATA[Edwards Lab]]></title>
  <description><![CDATA[
<p>We study the evolutionary biology of birds and relatives, combining field, museum and genomics approaches to understand the basis of avian diversity, evolution and behavior. Our guiding approaches include population genetics, which provides a quantitative framework for studying speciation, geographic variation and genome evolution; systematics, which acknowledges that the focal species of any study has relatives that are behaviorally and ecologically no less interesting; and natural history, which gives meaning to the genes and genomic patterns we study.</p>

<p>Lab page: http://www.oeb.harvard.edu/faculty/edwards/index.html</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37520/mmgenome-tools-for-extracting-individual-genomes-from-metagneomes</guid>
	<pubDate>Thu, 09 Aug 2018 17:41:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37520/mmgenome-tools-for-extracting-individual-genomes-from-metagneomes</link>
	<title><![CDATA[mmgenome: Tools for extracting individual genomes from metagneomes]]></title>
	<description><![CDATA[<p>The mmgenome toolbox enables reproducible extraction of individual genomes from metagenomes. It builds on the&nbsp;<a href="http://madsalbertsen.github.io/multi-metagenome/">multi-metagenome</a>&nbsp;concept, but wraps most of the process of extracting genomes in simple R functions. Thereby making the whole process of binning easy and at the same time reproducible through the Rmarkdown format.</p>
<p>The mmgenome R package also facilitates effortless integration with additional data sources and hence should not be seen as "yet another binning method", but rather a package to integrate different binning strategies.</p>
<p>All functions in the mmgenome R package has associated documentation, check it out in R by e.g.&nbsp;<code>?mmplot</code>.</p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/mmgenome" rel="nofollow">https://github.com/MadsAlbertsen/mmgenome</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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