<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31302?offset=530</link>
	<atom:link href="https://bioinformaticsonline.com/related/31302?offset=530" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/10409/check-linux-server-configuration</guid>
	<pubDate>Tue, 06 May 2014 01:10:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/10409/check-linux-server-configuration</link>
	<title><![CDATA[Check Linux server configuration !!]]></title>
	<description><![CDATA[<p>Bioinformatician uses servers for computational analysis. Sometime we need to check the server details before running our programs or tools. Here I am showing some basic commands using them you can gather the system/server information.<br /><br />To check what version of Operating System is installed on the server you can use the following commands:-<br />&nbsp;=================================================================<br />1.cat /etc/issue<br />[root@localhost ~]# cat /etc/issue<br />Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br />Kernel \r on an \m<br /><br />2.cat /etc/redhat-release<br />[root@localhost ~]# cat /etc/redhat-release<br />Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br /><br /><br />3.lsb_release -a<br />[root@localhost ~]# lsb_release -a<br />LSB Version:&nbsp;&nbsp;&nbsp; :core-3.1-ia32:core-3.1-noarch:graphics-3.1-ia32:graphics-3.1-noarch<br />Distributor ID: RedHatEnterpriseServer<br />Description:&nbsp;&nbsp;&nbsp; Red Hat Enterprise Linux Server release 5.5 (Tikanga)<br />Release:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5.5<br />Codename:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Tikanga<br /><br /><br /><br />To check whether the operating system is 32 or 64bit:-<br />================================<br /># uname -i<br />[root@localhost ~]# uname -i<br />i386<br />(i386 represents that server is having 32bit operating system)<br /><br />[root@localhost ~]# uname -i<br />x86_64<br />(x86_64 represents that server is having 64bit operating system)<br /><br />To see the processor/CPU information:-<br />=============================<br /># cat /proc/cpuinfo<br />[root@localhost ~] cat /proc/cpuinfo<br />processor&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />vendor_id&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : GenuineIntel<br />cpu family&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 6<br />model&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 15<br />model name&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : Intel(R) Xeon(R) CPU&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5130&nbsp; @ 2.00GHz<br />stepping&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 6<br />cpu MHz&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 1995.087<br />cache size&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 4096 KB<br />physical id&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />siblings&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 2<br />core id&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />cpu cores&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 2<br />apicid&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 0<br />fdiv_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />hlt_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />f00f_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />coma_bug&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : no<br />fpu&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : yes<br />fpu_exception&nbsp;&nbsp; : yes<br />cpuid level&nbsp;&nbsp;&nbsp;&nbsp; : 10<br />wp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : yes<br />flags&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe nx lm constant_tsc pni monitor ds_cpl vmx tm2 ssse3 cx16 xtpr lahf_lm<br />bogomips&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; : 3990.17<br />(Here processor number 0 indicates that the system is having one process(processor number starts with zero))<br /><br /><br /><br /><br />To check memory information:-<br />===========================<br /># free -m<br />[root@localhost ~]# free -m<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; total&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; used&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; free&nbsp;&nbsp;&nbsp;&nbsp; shared&nbsp;&nbsp;&nbsp; buffers&nbsp;&nbsp;&nbsp;&nbsp; cached<br />Mem:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5066&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 3513&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1552&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 612&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2319<br />-/+ buffers/cache:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 582&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 4484<br />Swap:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1983&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1983<br /><br /><br /><br /># cat /proc/meminfo<br />[root@localhost ~]# cat /proc/meminfo<br />MemTotal:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 5187752 kB<br />MemFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1639300 kB<br />Buffers:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 627024 kB<br />Cached:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2374944 kB<br />SwapCached:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />Active:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2458788 kB<br />Inactive:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 920964 kB<br />HighTotal:&nbsp;&nbsp;&nbsp;&nbsp; 4325164 kB<br />HighFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 1561936 kB<br />LowTotal:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 862588 kB<br />LowFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 77364 kB<br />SwapTotal:&nbsp;&nbsp;&nbsp;&nbsp; 2031608 kB<br />SwapFree:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2031608 kB<br />Dirty:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 704 kB<br />Writeback:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />AnonPages:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 377892 kB<br />Mapped:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 35328 kB<br />Slab:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 153036 kB<br />PageTables:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 6316 kB<br />NFS_Unstable:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />Bounce:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0 kB<br />CommitLimit:&nbsp;&nbsp; 4625484 kB<br />Committed_AS:&nbsp;&nbsp; 977132 kB<br />VmallocTotal:&nbsp;&nbsp; 116728 kB<br />VmallocUsed:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 4492 kB<br />VmallocChunk:&nbsp;&nbsp; 112124 kB<br />HugePages_Total:&nbsp;&nbsp;&nbsp;&nbsp; 0<br />HugePages_Free:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0<br />HugePages_Rsvd:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0<br />Hugepagesize:&nbsp;&nbsp;&nbsp;&nbsp; 2048 kB<br /><br /><br />To check the model and serial name of the server:-<br />=======================================<br />[root@localhost ~]#&nbsp; dmidecode | egrep -i "product name|Serial number"<br />Product Name: PowerEdge R710<br />Serial Number: AB8CDE1<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;<br /><br />To check the host name:-<br />=====================<br />[root@localhost ~]# uname -n<br />localhost<br /><br />[root@localhost ~]# hostname<br />localhost<br /><br />To check the kernel version:-<br />========================<br />[root@localhost ~]# uname -r<br />2.6.18-238.9.1.el5PAE</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</guid>
	<pubDate>Thu, 08 Aug 2024 23:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome</link>
	<title><![CDATA[Tools to access the quality of your assembled genome !]]></title>
	<description><![CDATA[<ul dir="auto">
<li><a href="https://github.com/linsalrob/fasta_validator">FASTA VALIDATOR</a>&nbsp;+&nbsp;<a href="https://github.com/shenwei356/seqkit">SEQKIT RMDUP</a>: FASTA validation</li>
<li><a href="https://genometools.org/tools/gt_gff3validator.html">GENOMETOOLS GT GFF3VALIDATOR</a>: GFF3 validation</li>
<li><a href="https://github.com/PlantandFoodResearch/assemblathon2-analysis/blob/a93cba25d847434f7eadc04e63b58c567c46a56d/assemblathon_stats.pl">ASSEMBLATHON STATS</a>: Assembly statistics</li>
<li><a href="https://genometools.org/tools/gt_stat.html">GENOMETOOLS GT STAT</a>: Annotation statistics</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS ADAPTOR</a>: Adaptor contamination pass/fail</li>
<li><a href="https://github.com/ncbi/fcs">NCBI FCS GX</a>: Foreign organism contamination pass/fail</li>
<li><a href="https://gitlab.com/ezlab/busco">BUSCO</a>: Gene-space completeness estimation</li>
<li><a href="https://github.com/tolkit/telomeric-identifier">TIDK</a>: Telomere repeat identification</li>
<li><a href="https://github.com/oushujun/LTR_retriever/blob/master/LAI">LAI</a>: Continuity of repetitive sequences</li>
<li><a href="https://github.com/DerrickWood/kraken2">KRAKEN2</a>: Taxonomy classification</li>
<li><a href="https://github.com/igvteam/juicebox.js">HIC CONTACT MAP</a>: Alignment and visualisation of HiC data</li>
<li><a href="https://github.com/mummer4/mummer">MUMMER</a>&nbsp;&rarr;&nbsp;<a href="http://circos.ca/documentation/">CIRCOS</a>&nbsp;+&nbsp;<a href="https://plotly.com/">DOTPLOT</a>&nbsp;&amp;&nbsp;<a href="https://github.com/lh3/minimap2">MINIMAP2</a>&nbsp;&rarr;&nbsp;<a href="https://github.com/schneebergerlab/plotsr">PLOTSR</a>: Synteny analysis</li>
<li><a href="https://github.com/marbl/merqury">MERQURY</a>: K-mer completeness, consensus quality and phasing assessment</li>
</ul>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10460/assistant-professor-at-jawaharlal-nehru-university-in-delhi</guid>
  <pubDate>Wed, 07 May 2014 00:29:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at Jawaharlal Nehru University in Delhi]]></title>
  <description><![CDATA[
<p>Advt. No. RC/48/2014</p>

<p>SCHOOL OF COMPUTATIONAL AND INTEGRATIVE SCIENCES (SC&amp;IS)</p>

<p>ESSENTIAL QUALIFICATION : - M.Sc./M.Tech. in Physics/ Chemistry/ Biology/ Mathematics/ Statistics/ Bioinformatics/ Computational Biology. Ph.D. in the broad areas of Bioinformatics/ Computational Biology. Candidates must have demonstrated capabilities in terms of high impact research publications in either of the above mentioned areas.</p>

<p>Scale of Pay : - 15600-39100/- (PB-III) AGP Rs. 6000/-</p>

<p>For more details on Centre/School, Specializations etc. please visit JNU website www.jnu.ac.in or contact Section Officer, Room Nos. 131-132, Recruitment Cell, Administrative Block, JNU, New Delhi – 110067, Email: recruitmentjnu2013@gmail.com The last date for the receipt of application is 15 May, 2014.</p>

<p>http://www.jnu.ac.in/Career/</p>

<p>http://www.jnu.ac.in/Career/ADVTNo_RC_48_2014.pdf<br />Last Apply Date:</p>

<p>15 May 2014</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44770/nvidia-and-arc-institute-unveil-evo-2-a-breakthrough-ai-for-dna-design</guid>
	<pubDate>Fri, 21 Feb 2025 10:39:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44770/nvidia-and-arc-institute-unveil-evo-2-a-breakthrough-ai-for-dna-design</link>
	<title><![CDATA[NVIDIA and Arc Institute Unveil Evo 2: A Breakthrough AI for DNA Design]]></title>
	<description><![CDATA[<p>NVIDIA and the Arc Institute have introduced <strong style="font-size: 12.8px;">Evo 2</strong>, a groundbreaking AI model designed to <strong style="font-size: 12.8px;">understand, predict, and generate DNA sequences</strong>. This marks a major advancement in computational biology, offering scientists an unprecedented tool to decode the genetic blueprint of life and even design entirely new biological systems.</p><h3><strong>The Power of Evo 2: AI Meets DNA</strong></h3><p>Evo 2 is <strong>the largest AI model for biology ever created</strong>, trained on an astonishing <strong>9.3 trillion DNA "letters"</strong> (nucleotides) carefully selected from genomes spanning the entire tree of life. This massive dataset ensures that Evo 2 can recognize patterns and relationships in genetic sequences at an unparalleled scale.</p><p>For the first time, scientists can <strong>design DNA with AI</strong>, moving beyond simple sequence analysis to active DNA generation. Evo 2 enables researchers to <strong>predict, modify, and even create entire genetic sequences</strong>, opening new possibilities in medicine, agriculture, and synthetic biology.</p><h3><strong>Decoding the Dark Genome</strong></h3><p>One of the biggest challenges in genetics is understanding the <strong>non-coding regions</strong> of DNA&mdash;vast stretches of the genome that do not code for proteins but play crucial roles in regulating gene expression. These regions control when and how genes are activated, influencing everything from development to disease.</p><p>Evo 2 is designed to <strong>decode these non-coding elements</strong>, helping researchers uncover their functions and use this knowledge to develop gene-based therapies, synthetic life forms, and precision agriculture solutions.</p><h3><strong>From Reading DNA to Writing It</strong></h3><p>To put Evo 2&rsquo;s impact into perspective:</p><ul>
<li><strong>Previous AI models could "read" DNA</strong> like a book, analyzing genetic sequences and identifying patterns.</li>
<li><strong>Evo 2 can "write" entirely new DNA</strong>, designing functional genes, chromosomes, and even full genomes from scratch.</li>
</ul><p>This means scientists can now <strong>engineer biological systems with AI</strong>, designing new proteins, metabolic pathways, and genetic circuits to address real-world challenges.</p><h3><strong>A Step Toward Generative Biology</strong></h3><p>The Arc Institute describes Evo 2 as a major step toward <strong>"generative biology"</strong>&mdash;a revolutionary approach where AI is used to create <strong>novel biological structures</strong> rather than just analyzing existing ones. This could lead to breakthroughs such as:</p><ul>
<li><strong>New medicines</strong>: AI-generated enzymes and proteins tailored for targeted therapies.</li>
<li><strong>Disease-resistant crops</strong>: Genetically optimized plants for higher yield and climate resilience.</li>
<li><strong>Synthetic organisms</strong>: Custom-designed microbes for bioremediation, biofuel production, and industrial applications.</li>
</ul><h3><strong>An Open-Source Revolution</strong></h3><p>Unlike many proprietary AI models, <strong>Evo 2 is open source</strong>, making its capabilities accessible to researchers worldwide. This democratization of AI-driven biology means that scientists from different disciplines can <strong>collaborate, experiment, and innovate</strong>, accelerating discoveries in genetic engineering and synthetic biology.</p><p>With Evo 2, the boundaries of what&rsquo;s possible in <strong>DNA design, genetic engineering, and biological innovation</strong> are being redrawn. The future of life sciences is no longer just about understanding life&rsquo;s code&mdash;it&rsquo;s about writing it.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<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. 

Watch More DNews on TestTube http://testtube.com/dnews

Subscribe now! http://www.youtube.com/subscription_center?add_user=dnewschannel

DNews on Twitter http://twitter.com/dnews

Anthony Carboni on Twitter http://twitter.com/acarboni

Laci Green on Twitter http://twitter.com/gogreen18

Trace Dominguez on Twitter http://twitter.com/trace501

DNews on Facebook http://facebook.com/dnews

DNews on Google+ http://gplus.to/dnews

Discovery News http://discoverynews.com]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45251/aurora-a-new-detective-for-bacterial-genomes</guid>
	<pubDate>Fri, 21 Aug 2026 11:31:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45251/aurora-a-new-detective-for-bacterial-genomes</link>
	<title><![CDATA[Aurora: A New Detective for Bacterial Genomes]]></title>
	<description><![CDATA[<p>Imagine trying to solve a mystery with thousands of clues&mdash;but some of the clues are labelled incorrectly.</p><p>That is the challenge researchers face when studying how bacteria adapt to different environments. A bacterial gene may appear to be linked to a particular habitat, when the real reason is simply that closely related bacteria happen to live there.</p><p>In their 2025 Genome Biology paper, Bujdo&scaron;, Walter, and O&rsquo;Toole introduce aurora, a machine-learning tool designed to tackle this problem.</p><p>Aurora identifies potentially mislabeled or unusual bacterial strains before performing genome-wide association studies (GWAS). By cleaning up the dataset and accounting for bacterial evolutionary relationships, it can help researchers find genetic features that are more genuinely connected to habitat adaptation.</p><p>The researchers tested aurora using simulated and real bacterial datasets and found that it could recover important genetic associations even when datasets contained misleading labels.</p><p>The bigger lesson is simple: better biological discoveries often begin with better data.</p><p>Aurora gives researchers a new way to separate real genetic clues from misleading ones&mdash;and could help us better understand how bacteria adapt, survive, and evolve in the environments they call home.</p><p>Based on Bujdo&scaron; et al., &ldquo;aurora: a machine learning GWAS tool for analyzing microbial habitat adaptation,&rdquo; Genome Biology (2025).[Read the original paper](https://link.springer.com/article/10.1186/s13059-025-03524-7?)</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <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>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/45296/luo-lab-symbiosis-genomics-evolution</guid>
  <pubDate>Wed, 09 Sep 2026 03:30:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Luo Lab | Symbiosis Genomics &amp; Evolution]]></title>
  <description><![CDATA[
<p>We study the evolutionary genomics of marine invertebrates to understand their origins and diversity. Our lab combines high-throughput sequencing and single-cell transcriptomics to explore a wide range of non-model systems. We are particularly interested in how evolutionary novelty arises, with a focus on animal development and photosymbiosis.</p>

<p>Research Directions</p>

<p>Stony corals: evolution of novelty and photosymbiosis</p>

<p>Symbiotic acoels: cell type evolution and photosymbiosis</p>

<p>Animal genomes: structural evolution and gene regulation</p>

<p>https://sgel.biodiv.tw/home</p>
]]></description>
</item>
<item>
	<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>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</guid>
	<pubDate>Sat, 02 Jan 2021 07:05:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</link>
	<title><![CDATA[shovill: Assemble bacterial isolate genomes from Illumina paired-end reads]]></title>
	<description><![CDATA[<p><span>Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.</span></p><p>Address of the bookmark: <a href="https://github.com/tseemann/shovill" rel="nofollow">https://github.com/tseemann/shovill</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

</channel>
</rss>