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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28915?offset=940</link>
	<atom:link href="https://bioinformaticsonline.com/related/28915?offset=940" rel="self" type="application/rss+xml" />
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22026/igib-recruitment-2015-%E2%80%93-project-scientist</guid>
  <pubDate>Tue, 14 Apr 2015 12:19:59 -0500</pubDate>
  <link></link>
  <title><![CDATA[IGIB Recruitment 2015 – Project Scientist]]></title>
  <description><![CDATA[
<p>IGIB Recruitment 2015 – Project Scientist &amp; SPF Posts: CSIR – Institute of Genomics &amp; Integrative Biology (IGIB) has issued notification for the recruitment of Project Scientist, Sr Project Fellow vacancies on temporary basis for project entitled “Setting up of CSIR(unit)-TRISUTRA (Translational research and Innovative Science through Ayurgenomics)”. Eligible candidates may apply in prescribed application format on or before 23-04-2015. Other details like age limit, educational qualification, selection process &amp; how to apply are given below…</p>

<p>IGIB Vacancy Details:<br />Total No. of Posts: 04<br />Name of the Posts:<br />1. Project Scientist (Biology): 02 Posts<br />2. Project Scientist (Bioinformatics): 01 Post<br />3. Sr Project Fellow (Ayurveda): 01 Post</p>

<p>Age Limit: Candidates age should be 35 years for post 1, 32 years for post 2</p>

<p>Educational Qualification: Candidates should have Ph.D/ Ph.D submitted in any branch of Biological Science/ Life Science for post 1, Ph.D/ Ph.D submitted in Bioinformatics for post 2, BAMS degree with one year internship for post 3.</p>

<p>Selection Process: Candidates will be selected based on their performance in interview.</p>

<p>How to Apply: Eligible candidates may send their application along with all relevant documents on or before 23-04-2015.</p>

<p>Important Dates:<br />Last Date for Receipt of Application for Post 1 &amp; 2: 23-04-2015.<br />Date of Interview for Post 3: 27-04-2015.</p>

<p>For other details like pay scale, age relaxation, educational qualification, selection process, how to apply, etc., click on the link given below…</p>

<p>http://www.freejobalert.com/wp-content/uploads/2015/03/Notification-IGIB-Project-Scientist-SPF-Posts.pdf</p>

<p>http://www.igib.res.in/sites/default/files/27042015.pdf</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42188/tools-and-method-for-haplotype-phasing</guid>
	<pubDate>Fri, 04 Sep 2020 20:41:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42188/tools-and-method-for-haplotype-phasing</link>
	<title><![CDATA[Tools and Method for Haplotype phasing !]]></title>
	<description><![CDATA[<div>Huge amounts of genotype data are being produced with recent technological advances, both from increasingly&nbsp; comprehensive and inexpensive genome-wide SNP microarrays and from ever more accessible whole-genome and whole-exome sequencing methods. The vast amount of knowledge contained in these results, however, is best&nbsp; exploited through phased haplotypes, which classify the alleles co-located on the same chromosome. Since sequence and SNP array data normally take the form of unphased genotypes, one does not specifically observe which of the two parental chromosomes, or haplotypes, falls on a specific allele. Fortunately, new advances in both computational and laboratory methods promise improved determination of haplotype phase. Following are useful tools :</div><div>&nbsp;</div><p><strong>Arlequin:</strong>&nbsp;<a href="http://cmpg.unibe.ch/software/arlequin3/" target="_blank">http://cmpg.unibe.ch/software/arlequin3/</a></p><p><strong>BEAGLE:</strong>&nbsp;<a href="http://faculty.washington.edu/browning/beagle/beagle.html" target="_blank">http://faculty.washington.edu/browning/beagle/beagle.html</a></p><p><strong>fastPHASE:</strong>&nbsp;<a href="http://stephenslab.uchicago.edu/software.html" target="_blank">http://stephenslab.uchicago.edu/software.html</a></p><p><strong>GENEHUNTER:</strong>&nbsp;<a href="http://linkage.rockefeller.edu/soft/gh/" target="_blank">http://linkage.rockefeller.edu/soft/gh/</a></p><p><strong>The Genome Analysis Toolkit:</strong></p><p><a href="http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit" target="_blank">http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit</a></p><p><strong>IMPUTE2:</strong>&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html" target="_blank">https://mathgen.stats.ox.ac.uk/impute/impute_v2.html</a></p><p><strong>MACH:</strong>&nbsp;<a href="http://www.sph.umich.edu/csg/abecasis/MACH/" target="_blank">http://www.sph.umich.edu/csg/abecasis/MACH/</a></p><p><strong>MERLIN:</strong>&nbsp;<a href="http://www.sph.umich.edu/csg/abecasis/Merlin/" target="_blank">http://www.sph.umich.edu/csg/abecasis/Merlin/</a></p><p><strong>PHASE:</strong>&nbsp;<a href="http://stephenslab.uchicago.edu/software.html" target="_blank">http://stephenslab.uchicago.edu/software.html</a></p><p><strong>PL-EM:</strong>&nbsp;<a href="http://www.people.fas.harvard.edu/~junliu/plem/" target="_blank">http://www.people.fas.harvard.edu/~junliu/plem/</a></p><p><strong>&ldquo;Read-backed phasing&rdquo; algorithm</strong>:&nbsp;<a href="http://www.broadinstitute.org/gsa/wiki/index.php/Read-backed_phasing_algorithm" target="_blank">http://www.broadinstitute.org/gsa/wiki/index.php/Read-backed_phasing_algorithm</a></p><p><strong>SHAPE-IT:</strong>&nbsp;<a href="http://www.griv.org/shapeit/" target="_blank">http://www.griv.org/shapeit/</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/22047/binc-sample-question-paper</guid>
	<pubDate>Thu, 16 Apr 2015 09:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/22047/binc-sample-question-paper</link>
	<title><![CDATA[BINC Sample Question Paper !!!]]></title>
	<description><![CDATA[<p>BINC sample question paper round TWO.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/22047" length="1621" type="text/plain" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36395/ligand-docking-tools-and-software</guid>
	<pubDate>Wed, 25 Apr 2018 05:05:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36395/ligand-docking-tools-and-software</link>
	<title><![CDATA[Ligand Docking Tools and Software !]]></title>
	<description><![CDATA[<p>Ligand docking referred to cases where small molecule (&ldquo;ligand&rdquo;) is being docked into much larger macromolecule ("target"). The following is partial list of docking software, focusing on free (at least for academic institutes) and/or popular docking tools.&nbsp;</p><p><a href="http://autodock.scripps.edu/" target="_blank">AutoDock</a></p><p>Stochastic (GA)</p><p>Flexible ligand and partially flexible target</p><p><a href="http://www.arguslab.com/" target="_blank">ArgusLab</a></p><p>Systematic</p><p>Flexible ligandX-Score based</p><p><a href="http://dock.compbio.ucsf.edu/" target="_blank">DOCK</a></p><p>Systematic (IC)</p><p>Flexible ligandDOCK 3.5 (force field)</p><p><a href="http://www.simbiosys.ca/ehits/index.html" target="_blank">eHITS</a></p><p>Systematic (RBD of fragments followed by reconstruction)Flexible ligand and partially flexible targetHiTS_Score (empirical)</p><p><a href="http://www.biosolveit.de/" target="_blank">FlexX</a></p><p>Systematic (IC)Flexible ligandFlexX SF (empirical)Commercial</p><p><a href="http://flipdock.scripps.edu/" target="_blank">FLIPDock</a></p><p>Stochastic (GA)Flexible ligand and flexible targetAUTODOCK (empirical)</p><p><a href="http://www.eyesopen.com/products/applications/fred.html" target="_blank">FRED</a></p><p>Systematic (RBD)Flexible ligandChemScore, PLP, ScreenScore, ChemGauss (empirical/consensus)</p><p><a href="http://www.ccdc.cam.ac.uk/products/life_sciences/gold/" target="_blank">GOLD</a></p><p>Stochastic (GA)</p><p>Flexible ligand and partially flexible targetGoldScore, ChemScore (empirical), ASP (knowledge based)</p><p><a href="http://www.molsoft.com/docking.html" target="_blank">ICM</a></p><p>Stochastic (MC)</p><p>Flexible ligand and partially flexible targetICM SF (empirical)</p><p><a href="http://www.scfbio-iitd.res.in/dock/pardock.jsp" target="_blank">ParDOCK</a></p><p>Stochastic (MC)</p><p>RigidBAPPL (empirical)</p><p><em><a href="http://www.scfbio-iitd.res.in/dock/pardock.jsp" target="_blank"></a></em><a href="http://www.tcd.uni-konstanz.de/research/plants.php" target="_blank">PLANTS</a></p><p>Stochastic (ACO)Flexible ligand and partially flexible target</p><p>CHEMPLP, PLP (empirical)</p><p><a href="http://www.biopharmics.com/" target="_blank">Surflex</a></p><p>Systematic (IC/MA)Flexible ligandHammerhead based (empirical)</p><p>Point to note:</p><p>Several studies have shown that the performance of most docking tools is highly dependent on the particular characteristics of both the binding site and the ligand to be investigated, and the determination which method would be more suitable in a specific context is difficult. We encouraged you to check several docking methods to determine which one(s) work best for your system.</p><p>&nbsp;</p><p><a href="http://autodock.scripps.edu/" target="_blank"></a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22072/bioinformatics-jrfrasrf-position-at-indian-institute-of-science-education-and-research-iiser-kolkata-kolkata-west-bengal</guid>
  <pubDate>Fri, 17 Apr 2015 04:11:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/RA/SRF position at Indian Institute of Science Education and Research (IISER Kolkata) - Kolkata, West Bengal]]></title>
  <description><![CDATA[
<p>Research Position in Computational Biology in the group of Shree P. Pandey Positions available in the area of NGS data analysis, bioinformatics, plant genomics</p>

<p>Project Description: Projects involves high throughput analysis of data mostly generated by massively parallel sequencing (RNA-Seq and small-RNA-Seq), microarrays and related platforms. We are looking for highly motivated and bright individuals interested in high-throughput cutting-edge data analyses methods in genomics (computational positions). Available positions: Applications are invited from suitable candidates in both, the Max Planck India Partner Program and the CRP Wheat Program for openings at the levels:</p>

<p>Post Name-Qualification-Salary:<br />Project assistant – Master’s – Rs. 14000<br />Project fellow (junior data analyst) – Masters + research experience – Rs. 16000<br />Research fellow (senior data analyst) – Masters + adequate research experience/desirable skill sets – Rs. 22000<br />Research Associated – PhD (&lt; 1yr) /&gt; 1 yr experience – Rs. 28000 / Rs. 32000<br />Essential qualification: MSc/MTech/PhD (or other suitable qualification) in discipline related to bioinformatics, computational biology, computer application (or equivalent)/ ‘Advance Post-Graduate Diploma in Bioinformatics’. Proficiency in one of the programming languages or statistics (proficient in R for example) is compulsory.<br />Desirable qualification: 1. Programming experiences in at least one low level language such as C/C++ and one scripting language such as Perl/Python/PHP and knowledge of SQL/MySQL. 2. Substantial experience in the linux or other unix environments. 3. Experience of working in projects on Bioinformatics, Genetics or Biological application areas/Computational and Statistical analysis (e.g. using R or Matlab). Experience in the field of genomics (NGS, microarrays, genome annotation), database development and management, software development, systems and network biology (or related fields) will be preferred.<br />SELECTION PROCEDURE FOR INDIAN INSTITUTE OF SCIENCE EDUCATION AND RESEARCH (IISER KOLKATA) – RESEARCH ASSOCIATE &amp; MORE VACANCIES POST:</p>

<p>Candidates can apply on or before 30/04/2015<br />No Detailed information about the selection process is mentioned in the recruitment notification<br />HOW TO APPLY FOR RESEARCH ASSOCIATE &amp; MORE VACANCIES IN INDIAN INSTITUTE OF SCIENCE EDUCATION AND RESEARCH (IISER KOLKATA):</p>

<p>Applications should contain CV along with brief description (maximum 1 page) of research conducted (highlighting skills and experience) till now. Applications should be sent by email to Shree P. Pandey, Department of Biological Sciences, IISER-Kolkata, Mohanpur Campus, West Bengal within 2 weeks. Interviews will be scheduled within 10 days of closing of applications. E-mail: sppiiserkol@gmail.com, sppandey@iiserkol.ac.in<br />For more details visit: http://www.iiserkol.ac.in/~sppandey</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq</guid>
	<pubDate>Tue, 08 May 2018 04:23:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq</link>
	<title><![CDATA[Scallop: reference-based transcriptome assembler for RNA-seq]]></title>
	<description><![CDATA[<p>Scallop is an accurate reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts. Scallop achieves this improvement through a novel algorithm that can be proved preserving all phasing paths from reads and paired-end reads, while also achieves both transcripts parsimony and coverage deviation minimization.</p>
<p>Scallop paper has been published at&nbsp;<a href="https://www.nature.com/articles/nbt.4020"><span>Nature Biotechnology</span></a>. The datasets and scripts used in this paper to compare the performance of Scallop and other assemblers are available at&nbsp;<a href="https://github.com/Kingsford-Group/scalloptest"><span>scalloptest</span></a>.</p>
<p>Please also checkout the&nbsp;<span>podcast</span>&nbsp;about Scallop (thanks&nbsp;<a href="https://ro-che.info/">Roman Cheplyaka</a>&nbsp;for the interview). It is available at both&nbsp;<a href="https://bioinformatics.chat/scallop">the bioinformatics chat</a>&nbsp;and&nbsp;<a href="https://itunes.apple.com/us/podcast/the-bioinformatics-chat/id1227281398">iTunes</a>.</p>
<p>&nbsp;</p>
<p>https://github.com/Kingsford-Group/scallop</p><p>Address of the bookmark: <a href="https://github.com/Kingsford-Group/scallop" rel="nofollow">https://github.com/Kingsford-Group/scallop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22235/project-fellow-bioinformatics-at-central-drug-research-institute</guid>
  <pubDate>Mon, 27 Apr 2015 20:15:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow Bioinformatics at Central Drug Research Institute]]></title>
  <description><![CDATA[
<p>Project Fellow (Bioinformatics)<br />Central Drug Research Institute<br />Address: Chattar Manzil, M.G.Road, Kaisarbagh<br />Postal Code: 226001<br />City: Lucknow<br />State: Uttar Pradesh<br />Pay Scale: Rs.16,000/- (fixed) p.m.<br />Educational Requirements: M.Sc. in Bioinformatics with 55% marks for Gen. &amp; OBC and 50% marks for SC/ST candidates, Physically and Visually handicapped candidates<br />Experience Requirements: Experience in computer-assisted scientific research in the area of Drug Design including Bio- molecular modeling and simulation studies, Virtual screening, pharmacophore perception, QSAR etc. Familiarity with Linux/Unixbased computer systems and required to participate and contribute to the development and application of computational models for the design and discovery of novel molecules as inhibitors or chemical probes<br />Details will be available at: http://cdriindia.org/uploaded/advt_no01-2015.pdf</p>

<p>How To Apply: Eligible candidates required to report for the Interview at 9:00 A.M. sharp on 11-05-2015 (For Position Code No. 001 to 009) and 12-05-2015 (For Position Code No. 010 to 016). Candidates reporting after 10:00 A.M will not be allowed to attend the interview. Eligible candidates may appear before the Selection Committee for interview on the date and time mentioned above at CDRI, B.S. 10/1, Sector 10, Jankipuram Extension, Sitapur Road, Lucknow-226031. Eligible candidates must bring with them duly filled up application form (which can be downloaded from our website www.cdriindia.org), along with Original certificates as well as attested copies of certificates of examinations starting from matriculation, date of birth, caste certificate (in case of SC/ST/OBC) experience certificate, publication, if any and recent passport size photograph etc. Original documents are essential for verification of the particulars quoted by the candidate in the application form and candidate failed to produce original documents at the time of verification, shall not be allowed to attend the interview. Any request for relaxation in this regard shall not be entertained.<br />Detail of Interview: 11-05-2015<br />Age Limit: 28 Years</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43896/list-of-comparative-genomics-resources</guid>
	<pubDate>Tue, 28 Jun 2022 04:08:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43896/list-of-comparative-genomics-resources</link>
	<title><![CDATA[List of comparative genomics resources !]]></title>
	<description><![CDATA[<div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1096638041"><span>3D-GENOMICS -- A Database to Compare Structural and Functional Annotations of Proteins between Sequenced Genomes</span></a></div><p>Compare structural and functional annotations of proteins between sequenced genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1100640374"><span>ARED Organism -- expansion of ARED reveals AU-rich element cluster variations between human and mouse</span></a></div><p>View AREs in the human transcriptome and study the comparative genomics of AREs in model organisms.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1234973128"><span>ATGC -- Alignable Tight Genomic Clusters Database</span></a></div><p>Find information about orthologous genes in prokaryotes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174596104"><span>AnimalQTLdb -- a livestock QTL database tool set for positional QTL information mining and beyond</span></a></div><p>Search for publicly available QTL data on livestocks and animal species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20110518150135"><span>BGDB -- Bovine Genome Database</span></a></div><p>Find information about bovine genomics data.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1229012662"><span>COMPARE -- a multi-organism system for cross-species data comparison and transfer of information</span></a></div><p>A multi-organism web-based resource system designed to easily retrieve, correlate and interpret data across species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1218141952"><span>CONDOR -- COnserved Non-coDing Orthologous Regions</span></a></div><p>A database resource of developmentally associated conserved non-coding elements.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1099057221"><span>CORG -- A database for COmparative Regulatory Genomics</span></a></div><p>Delineate conserved non-coding blocks from upstream regions of putative orthologous gene pairs from man, mouse, rat, fugu, Mus musculus, Danio rerio, and zebrafish.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1203608896"><span>COXPRESdb -- a database of coexpressed gene networks in mammals</span></a></div><p>Find coexpressed gene lists and networks in human and mouse.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1097763045"><span>CVTree -- A Phylogenetic Tree Reconstruction Tool Based on Whole Genomes</span></a></div><p>Construct phylogenetic tree of microorganisms based on oligopeptide content of their complete proteomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1232729680"><span>CleanEST -- the cleansed EST libraries database</span></a></div><p>A novel database server that classifies GenBank's dbEST (database of expressed gene sequences) libraries and removes contaminants.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1256926144"><span>CoCoa -- COefficient of COAncestry software</span></a></div><p>Find information about the ancestral relationship between genes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1227549154"><span>CoGemiR -- a comparative genomics microRNA database</span></a></div><p>Provides an overview of the genomic organization of microRNAs and extent of conservation during evolution in different metazoan species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1117678221"><span>Comparative Genometrics (CG) -- a database dedicated to biometric comparisons of whole genomes</span></a></div><p>Conduct comparative biometric analysis of chromosomes of different organisms.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1151007916"><span>DoTS -- Database Of Transcribed Sequences</span></a></div><p>Search for Indices of gene and transcripts in human and mouse.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174510065"><span>DroSpeGe -- rapid access database for new Drosophila species genomes</span></a></div><p>Search and compare 12 new and old Drosophila genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1098208414"><span>ECR Browser -- A Tool for Visualizing and Accessing Data from Comparisons of Multiple Vertebrate Genomes</span></a></div><p>Access to whole genome alignments of human, mouse, rat and fish sequences.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209738459"><span>EPGD -- Eukaryotic Paralog Group Database</span></a></div><p>Find eukaryotic paralog/paralogon information.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1232726869"><span>EVOG -- evolutionary visualizer for overlapping genes</span></a></div><p>Analyze the evolutionary process of overlapping genes when comparing different species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1227633714"><span>GNAT -- Inter-species gene mention normalization (ISGN)</span></a></div><p>The first publicly available system reported to handle inter-species gene mention normalization.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1229438992"><span>GenColors -- annotation and comparative genomics of prokaryotes made easy</span></a></div><p>A web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1151086258"><span>GeneNest gene indices</span></a></div><p>Visualize gene indices of human, mouse, Arabidopsis, Zebrafish, Drosophila and Sheep.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174489378"><span>GenomeTrafac -- a whole genome resource for the detection of transcription factor binding site clusters associated with conventional and microRNA encoding genes conserved between mouse and human gene orthologs</span></a></div><p>Use comparative genomics approach to characterize gene models and identify putative cis-regulatory regions of RefSeq Gene Orthologs.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20110518150753"><span>IKMC -- International Knockout Mouse Consortium web portal</span></a></div><p>Find information about mutated mouse genes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209411604"><span>IMG/M -- Integrated Microbial Genomes/Metagenomes</span></a></div><p>A data management and analysis system for metagenomes</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1234976694"><span>ISED -- Influenza sequence and epitope database.</span></a></div><p>Search for influenza sequence, vaccine, and drug resistance information.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20140710115515"><span>LAMDHI: The Search for Animal Models Starts Here</span></a></div><p>LAMHDI, the initiative to Link Animal Models to Human DIsease, is designed to accelerate the research process by providing biomedical researchers with a simple, comprehensive Web-based resource to find the best animal models for their research.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1228843803"><span>MANTIS -- a phylogenetic framework for multi-species genome comparisons</span></a></div><p>The missing link between multi-species full genome comparisons and functional analysis.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1099578148"><span>MBGD -- Microbial genome database for comparative analysis</span></a></div><p>Conduct comparative analysis of completely sequenced microbial genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1221077729"><span>MEGA -- Molecular Evolutionary Genetics Analysis</span></a></div><p>A biologist-centric software for evolutionary analysis of DNA and protein sequences.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174596756"><span>MamPol -- a database of nucleotide polymorphism in the Mammalia class</span></a></div><p>Conduct single nucleotide polymorphisms diversity measurements among homologous sequences from the Mammalia class.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1266437314"><span>MicrobesOnline -- Prokaryotic Genome Database</span></a></div><p>Find information about 1000s of microbial genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1208461006"><span>Narcisse -- a mirror view of conserved syntenies</span></a></div><p>A database dedicated to the study of genome conservation.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1219772764"><span>OMA -- the Orthologous MAtrix project</span></a></div><p>Explore orthologous relations across 352 complete genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209738741"><span>OPTIC -- orthologous and paralogous transcripts in clades</span></a></div><p>Browse complete genomes in several clades.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209573208"><span>OrthoDB -- the hierarchical catalog of eukaryotic orthologs</span></a></div><p>Find groups of orthologous genes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1221231200"><span>OrthoMaM -- orthologous mammalian markers</span></a></div><p>A database of orthologous genomic markers for placental mammal phylogenetics.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1100009979"><span>PEDANT -- Protein Extraction, Description and ANalysis Tool</span></a></div><p>Conduct genome wide functional and structural analysis.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174489475"><span>PReMod -- a database of genome-wide mammalian cis-regulatory module predictions</span></a></div><p>Conduct genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1151083092"><span>PhenomicDB -- Comparison of phenotypes of orthologous genes in human and model organisms</span></a></div><p>Compare phenotypes of a given gene or gene set in different model organisms.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1190899370"><span>Phylemon -- A suite of web tools for molecular evolution, phylogenetics and phylogenomics</span></a></div><p>Phylemon is a web server that integrates a selected suite of more than 20 different tools from the most popular stand-alone programs of phylogenetic and evolutionary analysis.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1232555615"><span>PhyloPat -- the phylogenetic pattern database</span></a></div><p>Use this database to see where in the evolution some phylogenetic lineages were started, and over which species they were contained.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174510223"><span>Pristionchus.org -- a genome-centric database of the nematode satellite species Pristionchus pacificus</span></a></div><p>Search for genomic information on nematode satellite species Pristionchus pacificus.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1236367352"><span>ProtClustDB -- NCBI Protein Clusters Database</span></a></div><p>Find information about related protein sequences.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209410278"><span>ProtozoaDB -- database of protozoan genomes</span></a></div><p>Database hosting genomics and post-genomics data from multiple protozoans.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1232554690"><span>Pseudofam -- the pseudogene families database</span></a></div><p>A database of pseudogene families based on the protein families from the Pfam database.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20110518151439"><span>RIDM - RIKEN Integrated Database of Mammals</span></a></div><p>Find genomic information about mammals.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1272562567"><span>RegPrecise -- Regulon Prediction Database</span></a></div><p>Find information about predicted regulons in prokaryotic transcription regulation.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1272477473"><span>SALAD -- Surveyed contained motif ALignment diagram and the Associating Dendrogram</span></a></div><p>Perform systematic comparison of proteome data among species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1229010765"><span>SGN -- SOL Genomics Network</span></a></div><p>A comparative map viewer dedicated to the biology of the Solanaceae family.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1256669040"><span>ShotgunFunctionalizeR -- R-package for functional comparison of metagenomes</span></a></div><p>Analyze data from functional analysis on fragmented microbial genetic material.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1256238439"><span>SnoopCGH -- Comparative Genomic Hybridization software</span></a></div><p>Visualize and explore comparative genomic hybridization data sets.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1174489598"><span>SwissRegulon -- a database of genome-wide annotations of regulatory sites</span></a></div><p>Search for genome-wide annotations of regulatory sites in yeast and prokaryotes genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1229013521"><span>TaxonGap -- a visualization tool for intra- and inter-species variation among individual biomarkers</span></a></div><p>Compare and select individual biomarkers.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1106063477"><span>The Adaptive Evolution Database (TAED) -- a phylogeny based tool for comparative genomics</span></a></div><p>Search for information on adaptive evolution in gene families of higher plants and chordate.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1216742716"><span>The CGView Server -- a comparative genomics tool for circular genomes</span></a></div><p>Generate graphical maps of circular genomes that show sequence features, base composition plots, analysis results and sequence similarity plots.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1099663588"><span>The ERGO -- Genome analysis and discovery system</span></a></div><p>Conduct a comprehensive analysis of genes and genomes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1177611772"><span>The Macaque Genome: Interactive Poster and Teaching Resource</span></a></div><p>An interactive online poster presentation on the Macaque genome, including high-quality images, video clips, and Web resources</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1103816940"><span>The TIGR Gene Indices -- clustering and assembling EST and known genes and integration with eukaryotic genomes</span></a></div><p>Search for annotated genetic information of expressed sequence tags (ESTs) in different eukaryotic organisms.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1043767169"><span>UniGene</span></a></div><p>Find mapping and expression information for a unigene cluster (ESTs and full-length mRNA sequences organized into clusters that each represent a unique known or putative gene)</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1216738072"><span>Uprobe -- universal overgo hybridization-based probe retrieval and design</span></a></div><p>A public online resource for identifying or designing 'universal' overgo-hybridization probes from conserved sequences that can be used to efficiently screen one or more genomic libraries from a designated group of species.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1098205291"><span>VISTA -- Computational Tools for Comparative Genomics</span></a></div><p>Comprehensive suite of programs and databases for comparative analysis of genomic sequences.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL20110518144404"><span>cBARBEL -- Catfish Breeder and Researcher Bioinformatics Entry Location</span></a></div><p>Find information about ictalurid catfish.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1209738040"><span>eggNOG -- evolutionary genealogy of genes: Non-supervised Orthologous Groups</span></a></div><p>Discover orthologous groups of genes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1234370319"><span>metaTIGER -- a metabolic gene evolution resource</span></a></div><p>Find metabolic networks and phylogenomic information on a taxonomically diverse range of eukaryotes.</p></div><div><div><a href="https://www.hsls.pitt.edu/obrc/index.php?page=URL1138901833"><span>xBASE -- a collection of online databases for bacterial comparative genomics</span></a></div><p>Conduct bacterial comparative genomics.</p></div>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22269/school-of-life-sciences-jawaharlal-nehru-university-vacancy-of-jrf-srf-ra-in-csir-funded-project</guid>
  <pubDate>Wed, 29 Apr 2015 21:26:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[School of Life Sciences, Jawaharlal Nehru University vacancy of JRF / SRF / RA in CSIR funded Project]]></title>
  <description><![CDATA[
<p>School of Life Sciences, Jawaharlal Nehru University has issued notification dated 27.04.2015 to fill the vacancy of JRF / SRF / RA in CSIR funded Projec entitled "Structural and functional characterization of serine biosynthetic pathway enzymes from entamoeba histolytica". It is good chance to get job with IITKGP and brighten your future. Learn eligibility criteria and apply on or before 08.05.2015.</p>

<p>Employer:	Jawaharlal Nehru University<br />Address:	Dr. S. Gourinath, Principal Investigator, School Of Life Sciences, Jawaharlal Nehru University, New Delhi-110067<br />Email:	not mentioned / provided for this job post<br />URL:	http://www.jnu.ac.in/Career/currentjobs.htm<br />Phone:	011 2674 2575<br />Skills:	not mentioned / required for this job post<br />Experience:	Experience in molecular biology, structural biology and bioinformatics is desired<br />Education:	M.Sc. in any field of life sciences.<br />Job Location:	New Delhi, Delhi, India   (View Jobs in New Delhi,   Jobs in Delhi,   Jobs in India)</p>

<p>Job Description: School of Life Sciences, Jawaharlal Nehru University vacancy of JRF / SRF / RA in CSIR funded Projec</p>

<p>Name of the Post: JRF / SRF / RA</p>

<p>Salary: As per rules</p>

<p>Required Job Profile:</p>

<p>Candidate must possess M.Sc. in any field of life sciences.</p>

<p>Desired Job Profile:</p>

<p>Candidate having NET - CSIR or UGC and experience in molecular biology, structural biology and bioinformatics is desired and experience with publication is preferred.</p>

<p>How to apply:</p>

<p>Eligible and interested candidates should need to apply with complete details to the above mentioned address on or before 08.05.2015.</p>

<p>Refer to http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45343/simulating-the-unseen-new-tools-reshaping-metagenomic-research</guid>
	<pubDate>Wed, 23 Sep 2026 09:42:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45343/simulating-the-unseen-new-tools-reshaping-metagenomic-research</link>
	<title><![CDATA[Simulating the Unseen: New Tools Reshaping Metagenomic Research]]></title>
	<description><![CDATA[<p>When benchmarking a new metagenomic pipeline the first step is generally to face a simple problem. A bioinformatician might have a good deal of real sequencing data, but there's a drawback in that the actual biological composition underlying those reads is almost never known. What organisms really were there? In what quantities? How many sequencing errors occurred? Can the pipeline correctly reconstruct the community? Since the true answers are unknown, it is difficult to deal with these questions.</p><p>Metagenomic simulators are a way of dealing with this issue; they produce artificial sequencing datasets in which both the composition of the microorganisms and the expected results are known. Researchers can then test a pipeline on such a controlled dataset and see precisely how well it functions. However, as metagenomic studies have become larger, more diverse, and more complex, simply generating artificial reads is no longer sufficient. The simulators now have to replicate community variation, sequencing errors, different sequencing platforms, massive data volumes, and even laboratory-based biases.</p><p>MIDASim (2024) was designed with a particular emphasis on microbial community dynamics. Unlike previous tools which regarded each simulated sample as individual, MIDASim is able to efficiently generate realistic multi-sample microbiome datasets, covering the cases where changes over time are being tracked. This feature is particularly useful when investigating how microbial communities vary between people, different experimental setups, or at various times. By overcoming the computational limitations of earlier simulation methods, MIDASim has made it easier to carry out large and complex microbiome simulation studies.</p><p>A major challenge is scale. Since modern metagenomic projects can involve millions or even billions of sequencing reads, generating such large synthetic datasets can become a significant computational problem. In order to tackle this issue, Izzy (2025) was developed. As a high-throughput metagenomic read simulator, Izzy is designed with speed in mind while still reproducing the typical patterns of sequencing errors. The people who developed it stated that it can be as much as 60 times faster than earlier tools, which makes large-scale simulations far more practical. Now, researchers can begin to ask not how long a simulation will take but rather what size dataset they want to test.</p><p>At the same time, the sequencing technology became more diverse. Researchers were not any longer restricted to using Illumina short reads since Oxford Nanopore and PacBio long-read sequencing also became important in the field of metagenomic research. In order to address these new requirements, MeSS (Metagenomic Sequence Simulator, 2025) was developed. The programme is based on a Snakemake framework and is therefore compatible with the Illumina, Oxford Nanopore and PacBio platforms. MeSS has also been designed to operate efficiently and to use less memory than earlier tools; it provides ready-made templates for the microbiomes of different sites in the human body, thus giving researchers a simple means of beginning to generate realistic simulated communities.</p><p>The simulation problem became even more specialized. Suppose that sequencing is not based on uniform sampling of DNA? In the case of targeted sequencing and hybridization-capture experiments, particular sequences are deliberately enriched, and the probability of capturing a target depends on both the probe and the target sequence. A standard model based on uniform sampling might fail to take into account this important feature of real experiments. That is why RAmpSim has been designed specifically to handle simulations for capture-based and targeted sequencing. Instead of depending solely on the assumption of uniform sampling, it includes a thermodynamic nearest-neighbor energy model to represent probe&ndash;target interactions and sequence-dependent enrichment. As a result, it is especially suitable for applications such as hybridization capture in metagenomics, where the efficiency of recovering a sequence can depend strongly on how it relates to the capture probes. RAmpSim thus reflects a wider trend towards simulations that aim not only to reproduce sequencing output but also key aspects of the experimental process itself.</p><p>MIDASim, Izzy, MeSS and RAmpSim all demonstrate how fast metagenomic simulation is evolving. MIDASim is able to deal with realistic variation within a large number of and changing microbial communities. Izzy overcomes the problem of generating very large datasets. MeSS provides support for a number of sequencing technologies in an efficient and repeatable manner. RAmpSim increases the experimental realism for capture-based sequencing. Although each of these tools addresses a separate issue, they all contribute to advancing the field.</p><p>Modern metagenomic simulation therefore aims not only at producing artificial FASTQ files. Researchers nowadays desire simulated datasets that reflect community changes, incorporate the characteristics of the sequencing platform, include real error patterns, take into account computational scale, and account for experimental biases. As metagenomic workflows become more advanced, the simulators have to keep up with this development. The tools are now going beyond that of simple data generators; they produce controlled versions of complex metagenomic experiments and thus provide researchers with something that ordinary sequencing data seldom does: a dataset in which the answer is known before any analysis takes place.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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