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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42499?offset=410</link>
	<atom:link href="https://bioinformaticsonline.com/related/42499?offset=410" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44516/16srna-database-download</guid>
	<pubDate>Wed, 24 Apr 2024 04:33:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44516/16srna-database-download</link>
	<title><![CDATA[16sRNA Database Download]]></title>
	<description><![CDATA[<p>Downloading 16S rRNA databases can be crucial for various bioinformatics analyses, especially in microbiome research. However, it's important to note that databases can vary based on your specific needs, such as the taxonomic coverage you require or the type of analysis you're performing. Here's a general guideline on how you can obtain 16S rRNA databases:</p><ol>
<li>
<p><span>NCBI (National Center for Biotechnology Information)</span>:</p>
<ul>
<li>NCBI provides various databases related to genetic information, including 16S rRNA sequences.</li>
<li>You can access the 16S ribosomal RNA sequences from NCBI's Nucleotide database (<a href="https://www.ncbi.nlm.nih.gov/nucleotide/" target="_new">https://www.ncbi.nlm.nih.gov/nucleotide/</a>).</li>
<li>Perform a search using keywords like "16S rRNA" or specific bacterial names to find relevant sequences.</li>
<li>You can download sequences individually or in batches using the provided tools.</li>
</ul>
</li>
<li>
<p><span>GreenGenes</span>:</p>
<ul>
<li>GreenGenes is a widely used 16S rRNA gene sequence database.</li>
<li>You can access it at <a target="_new">http://greengenes.secondgenome.com/</a>.</li>
<li>GreenGenes provides precompiled databases for various purposes, including classification, alignment, and phylogenetic analysis.</li>
</ul>
</li>
<li>
<p><span>SILVA</span>:</p>
<ul>
<li>SILVA (<a href="https://www.arb-silva.de/" target="_new">https://www.arb-silva.de/</a>) is another comprehensive database for ribosomal RNA (rRNA) sequences.</li>
<li>It covers not only 16S rRNA but also other ribosomal RNA sequences.</li>
<li>SILVA provides precompiled databases for various purposes, including taxonomic classification and alignment.</li>
</ul>
</li>
<li>
<p><span>Ribosomal Database Project (RDP)</span>:</p>
<ul>
<li>RDP (<a target="_new">http://rdp.cme.msu.edu/</a>) is a curated database that offers 16S rRNA sequences.</li>
<li>It provides tools for sequence analysis and classification.</li>
<li>You can download sequences and taxonomy information from their website.</li>
</ul>
</li>
<li>
<p><span>QIIME (Quantitative Insights Into Microbial Ecology)</span>:</p>
<ul>
<li>QIIME (<a href="https://qiime2.org/" target="_new">https://qiime2.org/</a>) is a widely used bioinformatics platform for microbiome analysis.</li>
<li>It provides tools for analyzing microbial communities, including processing 16S rRNA sequences.</li>
<li>QIIME often includes its own preprocessed 16S rRNA databases that can be used for analysis within the platform.</li>
</ul>
</li>
</ol><p>Before downloading any database, make sure to read the terms of use and citation requirements, as some databases may have specific usage policies. Additionally, consider the compatibility of the database with your analysis pipeline and software tools.</p><p>&nbsp;</p><p>NCBI 16s RNA database location&nbsp;ftp://ftp.ncbi.nih.gov/blast/db/16SMicrobial.tar.gz</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</guid>
	<pubDate>Sat, 10 May 2014 06:28:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</link>
	<title><![CDATA[Managing and Analyzing Next-Generation Sequence Data]]></title>
	<description><![CDATA[<p>Centralized Bioinformatics Core Facilities provide shared resources for the computational and IT requirements of the investigators in their department or institution. As such, they must be able to effectively react to new types of experimental technology. Recently faced with an unprecedented flood of data generated by the next generation of DNA sequencers, these groups found it necessary to respond quickly and efficiently to the informatics and infrastructure demands. Centralized Facilities newly facing this challenge need to anticipate time and design considerations of necessary components, including infrastructure upgrades, staffing, and tools for data analyses and management ...</p>
<p>More at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</p><p>Address of the bookmark: <a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369" rel="nofollow">http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12593/visiting-scientist-computational-genomics-two-positions</guid>
  <pubDate>Mon, 07 Jul 2014 22:53:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Visiting Scientist - Computational Genomics (two positions)]]></title>
  <description><![CDATA[
<p>Scientific/Managerial &amp; International Recruitment</p>

<p>ICRISAT seeks applications from Indian nationals Visiting Scientist-Computational Genomics (2 positions), to be part of a team of Centre of Excellence in Genomics (CEG), (www.icrisat.org/ceg) to work on legume genomics projects.  The positions will be based at ICRISAT’s Headquarters in Patancheru, Hyderabad, India.</p>

<p>ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. Covering 6.5 million square kilometers of land in 55 countries, the semi-arid tropics is home to over 2 billion people, with 650 million of these are the poorest of the poor. ICRISAT and its partners help empower those living in the semi-arid tropics, especially smallholder farmers, to overcome poverty, hunger, malnutrition and a degraded environment through more efficient and profitable agriculture. ICRISAT is headquartered in Greater Hyderabad, Andhra Pradesh, India and belongs to the Consortium of Centers supported by the Consultative Group on International Agricultural Research (CGIAR).</p>

<p>The Job: Responsibilities for these positions include:</p>

<p>    Analyzing and handling large-scale next generation sequencing DNA and RNA data<br />    Data mining and development of pipelines and troubleshooting<br />    Genome diversity analysis such as SNPs, Indels, Structural Variations, population structure<br />    Genome wide association study (GWAS) related analysis- LD analysis, hapmap and trait mapping<br />    Expression analysis based on RNA-Seq data, annotation, gene ontology and metabolic pathway analysis<br />    Epigenome analysis, small RNA identification<br />    Gene family analysis, sequence level protein analysis, orthology/paralogy and molecular modelling<br />    Compiling and analysis of results, writing reports and research papers</p>

<p>The Person:  Ph.D. or MSc/MTech/PGDCA with two years research experience in Biotechnology, Computational biology, Agricultural/ Plant Biotechnology, Genetics, Molecular Biology or related discipline. Good knowledge of programming/scripting in at least two of following languages: Perl, C, C++, R, Shell Scripting and Python is plus.</p>

<p>How to apply: Please apply latest by 20 July 2014.  The application should include the name of the position applied for, a letter of motivation, a full Curriculum Vita (CV), and the names and contact information of three references that are knowledgeable of the candidate’s professional qualifications and work experience. Technical details and more information about these positions can be obtained from R.K.VARSHNEY@CGIAR.ORG. All applications will be acknowledged, however only short listed candidates will be contacted.</p>

<p>Apply here https://recruit.zoho.com/ats/Portal.na?digest=T642sgLYWZOStExJ77cPrcM*sIMGZETWw4yPxngbmHA-</p>
]]></description>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website</guid>
	<pubDate>Sun, 25 May 2014 14:43:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11030/r-programming-and-jobs-website</link>
	<title><![CDATA[R programming and Jobs website]]></title>
	<description><![CDATA[<p>Welcome to the R Jobs section of ProgrammingR.com. If your organization has an R employment opportunity that you would like to have posted here, submit it via the <a href="http://www.programmingr.com/contact" title="contact page">contact page</a>. Prospective employees: use the contact information provided in the position listing to apply or contact the hiring organization.</p><p>Address of the bookmark: <a href="http://www.programmingr.com/category/stype/r-job-listings/" rel="nofollow">http://www.programmingr.com/category/stype/r-job-listings/</a></p>]]></description>
	<dc:creator>Pragati Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43898/online-resources-on-must-read-papers-in-evolutionary-biology-for-a-literature-club</guid>
	<pubDate>Tue, 28 Jun 2022 07:29:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43898/online-resources-on-must-read-papers-in-evolutionary-biology-for-a-literature-club</link>
	<title><![CDATA[Online resources on must-read papers in evolutionary biology, for a literature club]]></title>
	<description><![CDATA[<pre>1.       *Nick Barton:*

- The textbook "Evolution" by Nick Barton, with resources for
  exploring the literature: Barton, N. H., Briggs, D. E. G., Eisen, J.
  A., Goldstein, D. B., &amp; Patel, N. H. (2007). Evolution. Cold Spring
  Harbor Laboratory Press.

- Papers from a course named "Classics in Evolutionary Biology":

Evolutionary Synthesis
1. Haldane, J. B. S. 1932. The causes of evolution. Longmans. New York.
   (esp. Ch. IV).
2. Fisher, R. A. 1930. The genetical theory of natural selection. Oxford
   University Press, Oxford. Selected Sections - Fundamental Theorem.

Genetic Variation
1a. Lewontin, R. C., and J. L. Hubby. 1966. A molecular approach to
the study of genic heterozygosity in natural populations. II. Amount
of variation and degree of heterozygosity in natural populations of
Drosophila pseudoobscura. Genetics. 54:595-609.

1b. Sachidandam et al. 2001. A map of human genome sequence variation
containing 1.42 million single nucleotide polymorphisms. 409: 928-33.

2. Wright S., Dobzhansky T., Hovanitz W. 1942 Genetics of natural
populations VII The allelism of lethals in the third chromosome of
Drosophila pseudoobscura. Genetics 27: 363-394.

Recombination and evolution
1. Hill, W. G., and A. Robertson. 1966. The effect of linkage on limits
to artificial selection. Genet. Res. 8:269-294.

2. Maynard Smith and Haigh. 1974. The hitch-hiking effect of a favourable
gene. Genet. Res. 23: 23-35.

Understanding sequence variation
1. Begun D. J., Aquadro C. F., 1992 Levels of naturally occurring DNA
polymorphism correlate with recombination rate in Drosophila melanogaster.
Nature 356: 519-520.

2. Green R. E., Reich D., P&auml;&auml;bo S., 2010 A draft sequence of the
Neandertal genome. Science 328: 710-722.

Quantitative Genetics:  variation in complex traits
1. Galton F., 1877 Typical laws of heredity. Nature 15: 492-495-
512-514- 532-533.

2. Turelli M., 1984 Heritable genetic variation via
mutation-selection balance: Lerch's Zeta meets the abdominal
bristle. Theor. Popul. Biol. 25: 138-193.

Quantitative Genetics:  finding the genes
1. Shrimpton A. E., Robertson A., 1988 The Isolation of polygenic factors
controlling bristle score in Drosophila melanogaster II Distribution of
third chromosome bristle effects within chromosome sections. Genetics
118: 445-459.

2. Boyle E. A., Li Y. I., Pritchard J. K., 2017 An expanded view of
complex traits: from polygenic to omnigenic. Cell 169: 1177-1186.

Neutral Evolution
1. Kimura, M. 1968. Evolutionary rate at the molecular level. Science.
217:624-626.

2a. Kern A. D., Hahn M. W., 2018 The Neutral Theory in Light of Natural
Selection. Molecular Biology and Evolution 110: 21077-6.

2b. Jensen J. D., Payseur B. A., Stephan W., Aquadro C. F., Lynch M.,
Charlesworth D., Charlesworth B., 2018 The importance of the Neutral Theory
in 1968 and 50 years on: a response to Kern and Hahn 2018. Evolution 112:
2109-4.

2c. Ellegren &amp; Galtier. 2016. Determinants of genetic diversity. Nature
Reviews Genetics.

Mutation and Genetic Variability
1. Luria, S. E., and M. Delbr&uuml;ck. 1943. Mutations of Bacteria from Virus
Sensitivity to Virus Resistance. Genetics. 28(6):491-511.

2. Hill, W G. 1982. "Rates of Change in Quantitative Traits From Fixation
of New Mutations." Proceedings of the National Academy of Sciences (U.S.A.)
79: 142-45.

Testing for selection
1. McDonald &amp; Kreitman. 1991. Adaptive protein evolution at the Adh locus
in Drosophila. Nature.

2. Begun, et al. Mol. Biol. Evol. 16, 1816-1819 (1999).

3. Siddiq et al. 2016. Experimental test and refutation of a classic case
of molecular adaptation in Drosophila melanogaster.  Nature Ecology &amp;
Evolution.

The shifting balance
1. Wright, S. 1932. The roles of mutation, inbreeding, crossbreeding and
selection in evolution. Proceedings of the VI International Congress of
Genetics: 1. pp 356-366.

2. Coyne, J.A., N.H. Barton, and M. Turelli. 1997. A critique of Wright's
shifting balance theory of evolution.  Evolution 51: 643-671.

3. Barton. 2016. Sewall Wright on Evolution in Mendelian Populations and
the "Shifting Balance". Genetics.

Evolution of Sex
1.  Muller, H.J. 1964. The relation of recombination to mutational advance.
Mutation Res. 1(1):2-9

2. McDonald et al. 2016. Sex speeds adaptation by altering the dynamics of
molecular evolution. Nature.

Kin Selection, Cooperation, and Conflict
1. Hamilton, W. D. 1964. The genetical evolution of social behaviour I.
Journal of Theoretical Biology. 7:1-52.

2. Trivers, R. L. 1974 Parent-offspring conflict. American Zoologist.
14(1):249-264.

Sexual Selection
1. Zahavi, A. 1975. Mate selection - a selection of a handicap. J. Theor.
Biol. 53:205-214.

2. Kirkpatrick, M., and Ryan, M.J. 1991. The evolution of mating
preferences and the paradox of the lek. Nature. 350:33-38.

Fitness Landscapes
1. Dean, A. 1995. A Molecular Investigation of Genotype by Environment
Interactions. Genetics. 139:19-33.

2. Costanzo et al. 2010. The Genetic Landscape of a Cell. Science.

Speciation
1. Coyne, J. A., and H. A. Orr. 1989. Patterns of speciation in Drosophila.
Evolution. 43:362-381.

2. Corbett-Detig et al. 2013. Genetic incompatibilities are widespread
within species. Nature.

2.       *Marcos Antezana:*

Valen, L. v. 1975. Energy and Evolution. University of Chicago, Department
of Biology.

3.       *Remco Folkertsma:*

1. The work by Hopi Hoekstra on local adaptation and oldfield mice

2. Poelstra, J. W., Vijay, N., Bossu, C. M., Lantz, H., Ryll, B., M&uuml;ller,
I., ... &amp; Wolf, J. B. (2014). The genomic landscape underlying phenotypic
integrity in the face of gene flow in crows. Science, 344(6190), 1410-1414.

4.       *Joshka Kaufmann and Leslie Turner*

They offer us a link to 'papers every evolutionary biologist should read',
the papers are collected by Leslie Turner.
https://static1.squarespace.com/static/53e8cb7ce4b02c4bc3aeeee4/t/5ab8fcb670a6ad55c67fcdf4/1522072758665/EvoBioClassicsRefList.pdf

5.       *Sarah Stockwell*

Matt Ridley collected classic papers in evolutionary biology and printed
part of these papers in his book Evolution (see Matt Ridley. Evolution
(Univ. of Oxford Press, 2nd edition, 2004))</pre>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11181/perl-one-liner-for-bioinformatician</guid>
	<pubDate>Fri, 30 May 2014 05:49:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11181/perl-one-liner-for-bioinformatician</link>
	<title><![CDATA[Perl one-liner for bioinformatician !!!]]></title>
	<description><![CDATA[<p>With the emergence of NGS technologies, and sequencing data most of the bioinformaticians mung and wrangle around massive amounts of genomics text. There are several "standardized" file formats (FASTQ, SAM, VCF, etc.) and some tools for manipulating them (fastx toolkit, samtools, vcftools, etc.), there are still times where knowing a little bit of Perl onliner is extremely helpful.</p><p>Perl one-liners are small and awesome Perl programs that fit in a single line of code and they do one thing really well. These things include changing line spacing, numbering lines, doing calculations, converting and substituting text, deleting and printing certain lines, parsing logs, editing files in-place, doing statistics, carrying out system administration tasks, updating a bunch of files at once, and many more. Perl one-liners will make you the shell warrior. Anything that took you minutes to solve, will now take you seconds!<br /><br />perl -pe '$\="\n"'&nbsp; &nbsp;<br />#double space a file<br /><br />perl -pe '$_ .= "\n" unless /^$/' <br />#double space a file except blank lines<br /><br />perl -pe '$_.="\n"x7' <br />#7 space in a line.<br /><br />perl -ne 'print unless /^$/' <br />#remove all blank lines<br /><br />perl -lne 'print if length($_) &lt; 20' <br />#print all lines with length less than 20.<br /><br />perl -00 -pe '' <br />#If there are multiple spaces, delete all leaving one(make the file a single spaced file).<br /><br />perl -00 -pe '$_.="\n"x4' <br />#Expand single blank lines into 4 consecutive blank lines<br /><br />perl -pe '$_ = "$. $_"'<br />#Number all lines in a file<br /><br />perl -pe '$_ = ++$a." $_" if /./' <br />#Number only non-empty lines in a file<br /><br />perl -ne 'print ++$a." $_" if /./' <br />#Number and print only non-empty lines in a file<br /><br />perl -pe '$_ = ++$a." $_" if /regex/' <br />#Number only lines that match a pattern<br /><br />perl -ne 'print ++$a." $_" if /regex/' <br />#Number and print only lines that match a pattern<br /><br />perl -ne 'printf "%-5d %s", $., $_ if /regex/' <br />#Left align lines with 5 white spaces if matches a pattern (perl -ne 'printf "%-5d %s", $., $_' : for all the lines)<br /><br />perl -le 'print scalar(grep{/./}&lt;&gt;)' <br />#prints the total number of non-empty lines in a file<br /><br />perl -lne '$a++ if /regex/; END {print $a+0}' <br />#print the total number of lines that matches the pattern<br /><br />perl -alne 'print scalar @F' <br />#print the total number fields(words) in each line.<br /><br />perl -alne '$t += @F; END { print $t}' <br />#Find total number of words in the file<br /><br />perl -alne 'map { /regex/ &amp;&amp; $t++ } @F; END { print $t }' <br />#find total number of fields that match the pattern<br /><br />perl -lne '/regex/ &amp;&amp; $t++; END { print $t }' <br />#Find total number of lines that match a pattern<br /><br />perl -le '$n = 20; $m = 35; ($m,$n) = ($n,$m%$n) while $n; print $m' <br />#will calculate the GCD of two numbers.<br /><br />perl -le '$a = $n = 20; $b = $m = 35; ($m,$n) = ($n,$m%$n) while $n; print $a*$b/$m' <br />#will calculate lcd of 20 and 35.<br /><br />perl -le '$n=10; $min=5; $max=15; $, = " "; print map { int(rand($max-$min))+$min } 1..$n' <br />#Generates 10 random numbers between 5 and 15.<br /><br />perl -le 'print map { ("a".."z",&rdquo;0&rdquo;..&rdquo;9&rdquo;)[rand 36] } 1..8'<br />#Generates a 8 character password from a to z and number 0 &ndash; 9.<br /><br />perl -le 'print map { ("a",&rdquo;t&rdquo;,&rdquo;g&rdquo;,&rdquo;c&rdquo;)[rand 4] } 1..20'<br />#Generates a 20 nucleotide long random residue.<br /><br />perl -le 'print "a"x50'<br />#generate a string of &lsquo;x&rsquo; 50 character long<br /><br />perl -le 'print join ", ", map { ord } split //, "hello world"'<br />#Will print the ascii value of the string hello world.<br /><br />perl -le '@ascii = (99, 111, 100, 105, 110, 103); print pack("C*", @ascii)'<br />#converts ascii values into character strings.<br /><br />perl -le '@odd = grep {$_ % 2 == 1} 1..100; print "@odd"'<br />#Generates an array of odd numbers.<br /><br />perl -le '@even = grep {$_ % 2 == 0} 1..100; print "@even"'<br />#Generate an array of even numbers<br /><br />perl -lpe 'y/A-Za-z/N-ZA-Mn-za-m/' file <br />#Convert the entire file into 13 characters offset(ROT13)<br /><br />perl -nle 'print uc' <br />#Convert all text to uppercase:<br /><br />perl -nle 'print lc' <br />#Convert text to lowercase:<br /><br />perl -nle 'print ucfirst lc' <br />#Convert only first letter of first word to uppercas<br /><br />perl -ple 'y/A-Za-z/a-zA-Z/' <br />#Convert upper case to lower case and vice versa<br /><br />perl -ple 's/(\w+)/\u$1/g' <br />#Camel Casing<br /><br />perl -pe 's|\n|\r\n|' <br />#Convert unix new lines into DOS new lines:<br /><br />perl -pe 's|\r\n|\n|' <br />#Convert DOS newlines into unix new line<br /><br />perl -pe 's|\n|\r|' <br />#Convert unix newlines into MAC newlines:<br /><br />perl -pe '/regexp/ &amp;&amp; s/foo/bar/' <br />#Substitute a foo with a bar in a line with a regexp.</p><p>Reference/Sources:</p><p>http://genomics-array.blogspot.in/2010/11/some-unixperl-oneliners-for.html</p><p><a href="http://genomespot.blogspot.com/2013/08/a-selection-of-useful-bash-one-liners.html">http://genomespot.blogspot.com/2013/08/a-selection-of-useful-bash-one-liners.html</a></p><p><a href="http://biowize.wordpress.com/2012/06/15/command-line-magic-for-your-gene-annotations/">http://biowize.wordpress.com/2012/06/15/command-line-magic-for-your-gene-annotations/</a></p><p><a href="http://genomics-array.blogspot.com/2010/11/some-unixperl-oneliners-for.html">http://genomics-array.blogspot.com/2010/11/some-unixperl-oneliners-for.html</a></p><p><a href="http://bioexpressblog.wordpress.com/2013/04/05/split-multi-fasta-sequence-file/">http://bioexpressblog.wordpress.com/2013/04/05/split-multi-fasta-sequence-file/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1215/livestock-functional-genomics-summer-school-lfg-2013</guid>
  <pubDate>Fri, 02 Aug 2013 09:57:37 -0500</pubDate>
  <link></link>
  <title><![CDATA[Livestock Functional Genomics Summer School (LFG 2013)]]></title>
  <description><![CDATA[
<p>*Livestock Functional Genomics Summer School - Call for applications*</p>

<p>1st Livestock Functional Genomics Summer School (LFG 2013).</p>

<p>This School was designed for graduate students and early-stage researchers with interest in livestock genomics, who are engaged in projects that require knowledge in the field of computational biology.</p>

<p>Sixty selected participants will spend 13 days receiving theoretical and practical training in genomic data handling from internationally renowned experts.</p>

<p>After the course, the participant should understand the basis and the context of livestock big molecular data, and be able to manipulate high density genotypes, whole genome sequences and transcriptome data.</p>

<p>The Summer School will be held in Araçatuba-SP Brazil, from the 13th to the 21st of September 2013.</p>

<p>All accepted participants will have *expenses fully covered (air ticket, hotel and meals)*, including a free pass to the 5th International Symposium on Animal Functional Genomics http://www.isafg2013.org.br </p>

<p>Applicants will be selected based on their résumés. Application date is due by August 10th.  Results will be announced in August 12th.  </p>

<p>Please consult website: http://www.sciencesatellite.org.br/sschool</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11311/stephen-friend-the-hunt-for-unexpected-genetic-heroes</guid>
	<pubDate>Sat, 31 May 2014 14:31:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11311/stephen-friend-the-hunt-for-unexpected-genetic-heroes</link>
	<title><![CDATA[Stephen Friend: The hunt for "unexpected genetic heroes"]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/Yagdvqn2YMU" frameborder="0" allowfullscreen></iframe>What can we learn from people with the genetics to get sick — who don't? With most inherited diseases, only some family members will develop the disease, while others who carry the same genetic risks dodge it. Stephen Friend suggests we start studying those family members who stay healthy. Hear about the Resilience Project, a massive effort to collect genetic materials that may help decode inherited disorders.

TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and much more.
Find closed captions and translated subtitles in many languages at http://www.ted.com/translate

Follow TED news on Twitter: http://www.twitter.com/tednews
Like TED on Facebook: https://www.facebook.com/TED

Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23516/visual-machine-learning</guid>
	<pubDate>Wed, 29 Jul 2015 04:29:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23516/visual-machine-learning</link>
	<title><![CDATA[Visual machine learning !!!]]></title>
	<description><![CDATA[<p>In machine learning, computers apply <strong>statistical learning</strong> techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.</p>
<p>More at http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</p><p>Address of the bookmark: <a href="http://www.r2d3.us/visual-intro-to-machine-learning-part-1/" rel="nofollow">http://www.r2d3.us/visual-intro-to-machine-learning-part-1/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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