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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36483?offset=1200</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10749/memories-can-be-passed-down-through-dna</guid>
	<pubDate>Sat, 10 May 2014 21:24:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10749/memories-can-be-passed-down-through-dna</link>
	<title><![CDATA[Memories Can Be Passed Down Through DNA]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/tbPwzII_g6o" frameborder="0" allowfullscreen></iframe>The premise of Assassin's Creed is the reliving of other people's memories stored inside DNA. Well scientists have found that in mice, it actually happens! Anthony is joined by special guest and our friend Tara Long from Hard Science to explain how this process works, and if it might apply to humans as well.

Read More: 
Parental olfactory experience influences behavior and neural structure in subsequent generations
http://www.nature.com/neuro/journal/vaop/ncurrent/abs/nn.3594.html
"Using olfactory molecular specificity, we examined the inheritance of parental traumatic exposure, a phenomenon that has been frequently observed, but not understood."

What Is Epigenetics?
http://www.sciencemag.org/content/330/6004/611
"The cells in a multicellular organism have nominally identical DNA sequences (and therefore the same genetic instruction sets), yet maintain different terminal phenotypes. This nongenetic cellular memory, which records developmental and environmental cues (and alternative cell states in unicellular organisms), is the basis of epi-(above)-genetics."

Epigenetics
http://en.wikipedia.org/wiki/Epigenetics

Watch More:
How to Change Your Genes
https://www.youtube.com/watch?v=B5DU9lgbsSE
TestTube Wild Card
http://testtube.com/dnews/dnews-231-how-too-many-screens-affect-our-brain?utm_source=YT&utm_medium=DNews&utm_campaign=DNWC
Is Sexiness Hereditary?
https://www.youtube.com/watch?v=z6STRCncvM8
____________________

DNews is dedicated to satisfying your curiosity and to bringing you mind-bending stories & perspectives you won't find anywhere else! New videos twice daily. 

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Discovery News http://discoverynews.com]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</guid>
	<pubDate>Sun, 07 Mar 2021 00:32:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</link>
	<title><![CDATA[Ancient whole genome duplication (WGD) detection tools !]]></title>
	<description><![CDATA[<p>There are two methods for ancient WGD detection, one is collinearity analysis, and the other is based on the Ks distribution map. Among them, Ks is defined as the average number of synonymous substitutions at each synonymous site, and there is also a Ka corresponding to it, which refers to the average number of non-synonymous substitutions at each non-synonymous site.</p><p>At present, some people have posted articles about the analysis process of WGD. I searched for the keyword "wgd pipeline" and found the following:</p><p><strong>GenoDup: https:// github.com/MaoYafei/GenoDup-Pipeline</strong><br /><strong>https://peerj.com/articles/6303/</strong><br /><strong>WGDdetector: https:// github.com/yongzhiyang2 012/WGDdetector</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3</strong><br /><strong>wgd: https:// github.com/arzwa/wgd</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2#Sec1</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>GeNoGAP https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>https://github.com/dfguan/purge_dups</strong><br /><strong>https://www.biorxiv.org/content/10.1101/2020.01.24.917997v1</strong></p><p>This article introduces the usage of wgd.</p><p>Wgd cannot be installed directly with bioconda at present, so it is a little troublesome to install, because it depends on a lot of software. wgd depends on the following software</p><p><strong>BLAST</strong><br /><strong>MCL</strong><br /><strong>MUSCLE/MAFFT/PRANK</strong><br /><strong>PAML</strong><br /><strong>PhyML/FastTree</strong><br /><strong>i-ADHoRe</strong></p><p>But the good news is that most of the software it depends on can be installed with bioconda</p><blockquote><p>conda create -n wgd python=3.5 blast mcl muscle mafft prank paml fasttree cmake libpng mpi=1.0=mpich<br />conda activate wgd</p></blockquote><p>Here mpi=1.0=mpich is selected, because i-adhore depends on mpich. If openmpi is installed, an error will appear while loading shared libraries: libmpi_cxx.so.40: cannot open shared object file: No such file or directory</p><p>After that, the installation is much simpler</p><blockquote><p>git clone https://github.com/arzwa/wgd.git<br />cd wgd<br />pip install .<br />pip install git+https://github.com/arzwa/wgd.git<br />For i-ADHoRe, you need to register at http:// bioinformatics.psb.ugent.be /webtools/i-adhore/licensing/Agree to the license to download i-ADHoRe-3.0</p></blockquote><p>Since my miniconda3 installed ~/opt/, the installation path is so~/opt/miniconda3/envs/wgd/</p><blockquote><p>tar -zxvf i-adhore-3.0.01.tar.gz<br />cd i-adhore-3.0.01<br />mkdir -p build &amp;&amp; cd build<br />cmake .. -DCMAKE_INSTALL_PREFIX=~/opt/miniconda3/envs/wgd/<br />make -j 4 <br />make insatall</p></blockquote><p>Take the sugarcane genome Saccharum spontaneum L as an example. The genome is 8-ploid with 32 chromosomes (2n = 4x8 = 32)</p><p><strong>Download the tutorial for CDS and GFF annotation files</strong></p><blockquote><p><strong>mkdir -p wgd_tutorial &amp;&amp; cd wgd_tutorial</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.cds.fasta.gz</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.gff3.gz</strong><br /><strong>gunzip *.gz</strong></p></blockquote><p>First conda activate wgdstart our analysis environment, and then start the analysis</p><p>Step 1 : Use to wgd mclidentify homologous genes in the genome</p><blockquote><p>wgd mcl -n 20 --cds --mcl -s Sspon.v20190103.cds.fasta -o Sspon_cds.out</p></blockquote><p>Step 2 : Use to wgd ksdbuild Ks distribution</p><blockquote><p>wgd ksd --n_threads 80 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl Sspon.v20190103.cds.fasta</p></blockquote><p>Step 3 : If the quality of the genome is good, then wgd syncollinearity analysis can be used . It can help us find the collinearity block in the genome and the corresponding anchor point</p><blockquote><p>wgd syn --feature gene --gene_attribute ID \<br /> -ks wgd_ksd/Sspon.v20190103.cds.fasta.ks.tsv \<br /> Sspon.v20190103.gff3 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl</p></blockquote><p>&nbsp;For more reading - There are 9 sub-modules in WGD</p><ul>
<li><span>kde: KDE fitting to the Ks distribution</span></li>
<li><span>ksd: Ks distribution construction</span></li>
<li><span>mcl: BLASP comparison of All-vs-ALl + MCL classification analysis.</span></li>
<li><span><span>mix: Hybrid modeling of Ks distribution.</span></span></li>
<li><span>pre: preprocess the CDS file</span></li>
<li><span>syn: Call I-ADHoRe 3.0 to use GFF files for collinearity analysis</span></li>
<li><span>viz: draw histogram and density plot</span></li>
<li><span>wf1: Ks standard analysis procedure of the whole genome paranome (paranome), call mcl, ksd and syn</span></li>
<li><span>wf2: Ks standard analysis procedure of one-vs-one homologous gene (ortholog), call wcl and kSD</span></li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10773/bioinformatics-jrfsrf-position-at-national-research-centre-on-plant-biotechnology</guid>
  <pubDate>Sun, 11 May 2014 22:29:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY]]></title>
  <description><![CDATA[
<p>NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY<br />LBS, CENTRE, PUSA CAMPUS, IARI NEW DELHI<br />NEW DELHI – 110 012</p>

<p>WALK- IN –INTERVIEWS</p>

<p>Eligible candidates may appear in Walk-in-Interview on May 23, 2014 at 10 AM for the posts of Research Associates &amp; Senior Research Fellows (SRF) in the following DST/DBT/ICAR funded projects.</p>

<p>1 NPTC Project on Bioinformatics and Comparative Genomics</p>

<p>Research Associate (One)</p>

<p>Rs. 24000/- + 30% HRA for masters degree holder with more than 4 years experience</p>

<p>Essential: Ph D in Plant Molecular Biology &amp; Biotechnology/Genetics 0r Candidates who have already submitted their Ph D thesis in above subjects</p>

<p>Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.</p>

<p>Senior Research Fellow ( UGCCSIR/ DBT/ ICAR Net qualified only): (One)</p>

<p>Rs. 16000/- + 30% HRA and Rs. 18000+30 HRA from 3rd year onwards</p>

<p>Essential:</p>

<p>1. ICAR/ UGCCSIR/DBT Net qualified only</p>

<p>2. M. Sc. (with thesis) in Biotechnology, Life Sciences, Biosciences/ Bioinformatics, Genetics/ Plant Pathology with experience in molecular biology.</p>

<p>Or M.Sc with more than 3 years research experiences</p>

<p>3. B.Sc. Agriculture or Biology</p>

<p>Desirable:<br />1. M. Sc. with thesis<br />2. Experience in molecular biology, plant tissue culture<br />3. Bioinformatics knowledge is important</p>

<p>2 DST JC Bose National Fellowship</p>

<p>Research Associate (Bioinformatics) : One</p>

<p>Rs.22000/- + 30% HRA for 1 &amp; 2nd Yr., Rs. 23000+ 30% HRA for 3rd year and Rs. 24000+30% HRA for 4th &amp;5th yr</p>

<p>Essential: M Ph D in Plant Molecular Biology &amp; Biotechnology/Genetics</p>

<p>Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.</p>

<p>Age limit: Max.35 years (Age relaxation of 5 years for SC/ST &amp; women and 3 years for OBC)</p>

<p>The posts are purely temporary in nature and are co-terminus with the project. Initially the offer will be made for one year only and may be further extendable based on performance of the candidate. The interview will be held on May 23 , 2014 at 10:00 AM at NRCPB, LBS Building, Pusa Campus, IARI, New Delhi- 110012. The candidates must bring four copies of biodata (in the prescribed proforma), original certificates, attested photocopies of each of the certificates and an attested copy of recent passport size photograph. No. TA/DA would be given for the appearance in interview. Only the candidates having essential qualification would be entertained for the interviews. Short-listing of candidates based on academic merit and experience will be done in case of large number of applicants.</p>

<p>Advertisement: http://www.nrcpb.org/sites/default/files/Advertisement%20for%20RA%20and%20SRF%20Position.pdf</p>
]]></description>
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<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/12943/a-history-of-bioinformatics-in-the-year-2039</guid>
	<pubDate>Wed, 23 Jul 2014 06:37:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/12943/a-history-of-bioinformatics-in-the-year-2039</link>
	<title><![CDATA[A History of Bioinformatics (in the Year 2039)]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/uwsjwMO-TEA" frameborder="0" allowfullscreen></iframe><p>C. Titus Brown http://video.open-bio.org/video/1/a-history-of-bioinformatics-in-the-year-2039</p>]]></description>
	
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/11144/scientists-map-17294-proteins-produced-in-human-body</guid>
	<pubDate>Thu, 29 May 2014 01:57:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11144/scientists-map-17294-proteins-produced-in-human-body</link>
	<title><![CDATA[Scientists map 17,294 proteins produced in human body]]></title>
	<description><![CDATA[<p>Indian scientists missed the genomic profiling bus, but they've more than made up for it by creating the first human proteome map which is an extension of the genomic study. Till now, here is no direct equivalent for the human proteome. But recently two groups present mass spectrometry-based analysis of human tissues, body fluids and cells mapping the large majority of the human proteome.</p><p>The Indian scientists working in Bangalore, along with their American counterparts, have mapped more than 17,000 proteins in 30 organs of the human body. Just like the human genome was sequenced around the turn of the millennium, this is an equivalent mapping of the human proteome.<br /><br />The researcher estimated there are around 20,500 proteins in the human body. These scientists have profiled around 17,294, which account for around 84% of the total proteins. Apart from this, the team also traced around 2,500 of 3,000 proteins that had been categorised as "missing proteins".</p><p>The work, done by group of Indian scientists, and Johns Hopkins University, published in the renowned journal Nature ( http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html ). Of the 72 people who worked on the project, 46 are Indians.</p><p>Reference:</p><p>http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html</p><p>http://www.proteinatlas.org/ -The antibody-based Human Protein Atlas programme</p><p>http://www.humanproteomemap.org/ -Proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions.</p><p>https://www.proteomicsdb.org/ -Assembled protein evidence for 18,097 genes in ProteomicsDB</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel</guid>
	<pubDate>Fri, 30 May 2014 13:24:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel</link>
	<title><![CDATA[How to sequence the human genome - Mark J. Kiel]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/MvuYATh7Y74" frameborder="0" allowfullscreen></iframe>View full lesson: http://ed.ted.com/lessons/how-to-sequence-the-human-genome-mark-j-kiel

Your genome, every human's genome, consists of a unique DNA sequence of A's, T's, C's and G's that tell your cells how to operate. Thanks to technological advances, scientists are now able to know the sequence of letters that makes up an individual genome relatively quickly and inexpensively. Mark J. Kiel takes an in-depth look at the science behind the sequence.

Lesson by Mark J. Kiel, animation by Marc Christoforidis.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</guid>
	<pubDate>Sun, 01 Jun 2014 23:38:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11354/genomics-and-personalized-medicine</link>
	<title><![CDATA[Genomics and Personalized Medicine]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/pgHAXCMMcro" frameborder="0" allowfullscreen></iframe>(October 20, 2009) Michael Snyder, Professor of Genetics and Chair of the Department of Genetics at Stanford, discusses advances in gene sequencing, the impact of genomics on medicine, the potential for personalized medicine. and efforts at Stanford to further study these issues.

Stanford Mini Med School is a series arranged and directed by Stanford's School of Medicine, and presented by the Stanford Continuing Studies program. Featuring more than thirty distinguished, faculty, scientists and physicians from Stanford's medical school, the series offers students a dynamic introduction to the world of human biology, health and disease, and the groundbreaking changes taking place in medical research and health care.

Stanford University
http://www.stanford.edu

Stanford University School of Medicine
http://med.stanford.edu

Stanford Continuing Studies
http://continuingstudies.stanford.edu

Stanford University Channel on YouTube:
http://www.youtube.com/stanford]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11434/adhoc-bioinformatics-faculty-position-nit</guid>
  <pubDate>Tue, 03 Jun 2014 16:19:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Adhoc Bioinformatics Faculty Position @ NIT]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF TECHNOLOGY, DEPARTMENT OF BIOTECHNOLOGY, WARANGAL – 506 021, Andhra Pradesh</p>

<p>No.NITW/BT/2014/adhoc</p>

<p>APPLICATIONS ARE INVITED FOR THE APPOINTMENT OF ADHOC FACULTY ON CONTRACT BASIS IN THE DEAPARTMENT OF BIOTECHNOLOGY</p>

<p>Period of Contract: Initially the appointment is for one semester i.e., from July 2014 up to December 2014 only.</p>

<p>Essential Qualifications:</p>

<p>i) B. Tech or equivalent in Biotechnology/ Industrial Biotechnology/ Biochemical Engineering / Chemical Engg. Or M. Sc in Microbiology/ Botany/ Zoology/ Biochemistry/Biotechnology and ii) M. Tech or equivalent in Biotechnology/Industrial Biotechnology/Bioinformatics</p>

<p>Or</p>

<p>Integrated M. Tech in Biotechnology/Industrial Biotechnology/ Bioinformatics</p>

<p>Candidates must possess First class (60% aggregate marks or 6.5 CGPA) at B. Tech/ M. Sc and M. Tech.</p>

<p>Desirable: Ph. D Pay Package: All selected candidates shall be eligible for a consolidated pay of Rs.30, 000/- per month. Candidates with Ph. D shall be eligible for an additional amount of Rs.5, 000/- per month.</p>

<p>How to apply : Applications on plain paper with attested photocopies of certificate and bio data along with justification for eligibility should reach to the Head, Department of Biotechnology, National Institute of Technology, Warangal AP 506004 in the form of soft or hard copy on or before 21st June 2014 email : biotech_hod@nitw.ac.in</p>

<p>Intimation: No separate call letters will be sent to the candidates. All the eligible candidates will be notified in the institute web site on 23rd June 2014. All the eligible candidates are requested to report for the interview to the Head, Department of Biotechnology at 9:00 AM on 27th June 2014</p>

<p>Joining: Selected candidates will be informed and they are expected to join immediately.</p>

<p>Advertisement:</p>

<p>http://www.nitw.ac.in/nitw/announcements/2014/Bio-Adhoc%20Advt.%20May-2014.pdf</p>
]]></description>
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