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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31156?offset=820</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal</guid>
	<pubDate>Wed, 15 May 2024 14:24:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44537/the-atcc-genome-portal</link>
	<title><![CDATA[The ATCC Genome Portal]]></title>
	<description><![CDATA[<p><span>The ATCC Genome Portal (AGP,&nbsp;</span><a href="https://genomes.atcc.org/">https://genomes.atcc.org/</a><span>) is a database of authenticated genomes for bacteria, fungi, protists, and viruses held in ATCC&rsquo;s biorepository. It now includes 3,938 assemblies (253% increase) produced under ISO 9000 by ATCC. Here, we present new features and content added to the AGP for the research community.</span></p><p>Address of the bookmark: <a href="https://genomes.atcc.org/" rel="nofollow">https://genomes.atcc.org/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9859/bioinformatics-jrfsrf-position-at-university-of-hyderabad</guid>
  <pubDate>Tue, 15 Apr 2014 20:07:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at University of Hyderabad]]></title>
  <description><![CDATA[
<p>UNIVERSITY OF HYDERABAD SCHOOL OF LIFE SCIENCES </p>

<p>Applications are invited from qualified individuals for a JRF/SRF position (sponsored by DBT/DST) at Prof. Jagan Pongubala’s laboratory, University of Hyderabad. Dr. Pongubala’s laboratory is investigating the molecular pathways that control the development of innate and adaptive immune cell types utilizing a combination of genetic, molecular and computational approaches.</p>

<p>JRF/SRF</p>

<p>Masters degree in Bioinformatics  (M.Sc./M.Tech.)</p>

<p>Rs. 12,000+HRA<br />Rs. 16,000+HRA</p>

<p>Initial appointment is for one year and  subjected to renewal up to 2 years</p>

<p>Candidates selected for the above position would have a choice to work on computational biology or experimental  biology. Candidates interested to work on computational biology are expected to perform high-throughput sequencing  (NGS) data analysis and should have a strong background in Bioinformatics &amp; Computational Biology, good  programming skills particularly Perl, Python, R and work experience in Linux environment.</p>

<p>Candidates interested to work on experimental biology should have work experience in techniques that are routinely  used in molecular biology and mammalian cell culture. A basic knowledge of bioinformatics is also desired. </p>

<p>Applicants for the above positions should have a Masters degree (M.Tech/M.Sc) with an aggregate marks greater  than 70% or a 7.5 CGPA. Candidates having JRF-fellowship through CSIR/UGC/ICMR/DBT will be encouraged  to enroll into Ph.D. program. The interested candidates having excellent organizational skills and the ability to work  in a team environment with an aspiration to learn new techniques and explore new scientific areas are requested to generate their resume using the link https://cvmkr.com/CV/new#0 and forward to pongubalajagan@gmail.com</p>

<p>Review of applications will begin immediately and continue until the position is filled. Eligible candidates will be called for an interview. No TA/ DA will be paid for attending the interview or at the time of joining the post. Applicants should note that the appointment is purely temporary and subjected to renewal up to three years and there is no Right to Claim for any regular appointment with the University.</p>

<p>Corresponding address: Jagan Pongubala, Ph.D.<br />Department of Animal Sciences<br />School of Life Sciences, Room:S44<br />University of Hyderabad<br />Gachibowli, Hyderabad 500046</p>

<p>Advertisement: https://www.uohyd.ac.in/images/recruitment/jrf-srf_130414.pdf</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44503/entire-human-genome-sequencing</guid>
	<pubDate>Tue, 02 Apr 2024 01:19:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44503/entire-human-genome-sequencing</link>
	<title><![CDATA[Entire Human Genome Sequencing !]]></title>
	<description><![CDATA[<p>Cost-effective whole human genome sequencing has revolutionized the landscape of genetic research and personalized medicine by making comprehensive genetic analysis accessible to a wider population. Through advancements in sequencing technologies, such as next-generation sequencing (NGS), costs have significantly decreased, enabling researchers and healthcare providers to analyze an individual's complete genetic makeup with greater efficiency and affordability. This has profound implications for disease diagnosis, prognosis, and treatment, as it allows for the identification of genetic predispositions and the customization of healthcare interventions based on an individual's unique genetic profile. Moreover, as the cost continues to decline, the potential for population-scale genomic studies and large-scale screening programs becomes increasingly feasible, promising to further enhance our understanding of human genetics and improve healthcare outcomes on a global scale.</p><p>Here are few companies:</p><p>https://mynucleus.com/</p><p>https://myome.com/</p><p>https://nebula.org/whole-genome-sequencing-dna-test/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10124/jrf-at-bose-institute-kolkata</guid>
  <pubDate>Mon, 21 Apr 2014 19:41:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF at Bose Institute, Kolkata]]></title>
  <description><![CDATA[
<p>ADVT. No. S/BIC/01/2014-15</p>

<p>Bose Institute, Kolkata, invites applications from Indian Citizens for ONE (01) temporary position of Junior Research Fellow in the DBT sponsored project entitled, “Centre of Excellance (CoE) in Bioinformatics at Bose Institute”, running under Prof. Pinakpani Chakrabarti, Project Co-ordinatior, Bioinformatics Centre. The project is tenable upto 31.03.2017, but duration of the fellowship is one year only. The JRF will work with one of the faculty members of the center based on his / her motivation in any specific area on Bioinformatics.</p>

<p>Essential Qualification: 1st class M.Sc. / M.Tech degree in any stream of Chemical/ Biological Sciences with CSIR-UGC-NET-JRF / ICMR-JRF / DBT-JRF or CSIR-UGCNET- LS / GATE qualification.</p>

<p>Desirable qualification:</p>

<p>(i) Specialized knowledge in Organic / Physical chemistry.<br />(ii) Any exposure to research involving the small molecules (like drug) and / or protein structure determination or prediction.<br />(iii) Basic knowledge in computer programming, e.g. using FORTRAN, C, shell, perl etc.<br />(iv) Hands-on-experience on any of the following software : CHARMM/AMBER/NAMD/GROMACS,Gaussian/Gamess, Haddock/Autodock, Schrodinger etc. (or any other software serving similar purposes in molecular modeling)</p>

<p>Fellowship :</p>

<p>(i) Rs. 16,000/- p.m., plus admissible HRA &amp; Medical Benefit for M.Sc. with CSIRUGC NET-JRF/ICMR-JRF/DBT-JRF or M.Tech. with CSIR-UGC NETJRF/<br />ICMR-JRF/DBT-JRF/CSIR-UGC NET-LS/GATE<br />(ii) Rs. 12,000/- p.m., plus admissible HRA &amp; Medical Benefit for M.Sc. with CSIRUGC NET-LS/GATE</p>

<p>Age : Below 28 years as on the day on which the application is made (relaxable in case of SC/ST/OBC/WOMEN candidates only as per rule).</p>

<p>Interested and eligible candidates should apply on plain paper duly signed by them clearly mentioning the area of interest in research, possession of any desirable qualification (s) as mentioned above and quoting Advertisement No. on the envelop as well as application with complete Bio-data giving e-mail ID, Phone No. and details of qualification i.e. examination passed, year, division, percentage of marks, from Secondary onwards with attested copies of testimonials, addressed to the Registrar, Bose Institute, P-1/12, CIT Scheme VII-M, Kankurgachi, Kolkata-700054 on or before April 25, 2014.</p>

<p>The shortlisted candidates will be called for an interview. Applicants are advised to check our website for future updates.</p>

<p>Advertisement: www.boseinst.ernet.in/ADVT/14/p_2.pdf</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44766/genome-simulation-with-slim-and-msprime</guid>
	<pubDate>Fri, 31 Jan 2025 12:47:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44766/genome-simulation-with-slim-and-msprime</link>
	<title><![CDATA[Genome Simulation with SLiM and msprime]]></title>
	<description><![CDATA[<p>Genome simulation is an essential tool in population genetics, enabling researchers to model evolutionary processes and study genetic variation. Two widely used simulation tools in this field are <strong style="font-size: 12.8px;">SLiM</strong><span style="font-size: 12.8px; font-weight: normal;"> and </span><strong style="font-size: 12.8px;">msprime</strong><span style="font-size: 12.8px; font-weight: normal;">. While both serve different purposes, they can be used together with the </span><strong style="font-size: 12.8px;">slendr</strong><span style="font-size: 12.8px; font-weight: normal;"> framework to compare simulation outputs effectively.</span></p><h2>Overview of SLiM and msprime</h2><h3>SLiM: Forward Genetic Simulator</h3><p>SLiM is a <strong>free, open-source</strong> tool designed for forward genetic simulations. It allows researchers to model complex evolutionary scenarios, including selection, recombination, and demographic events, making it particularly useful for studying adaptation and selection in populations.</p><p><strong>Key Features of SLiM:</strong></p><ul>
<li>
<p>Simulates population evolution forward in time</p>
</li>
<li>
<p>Supports custom evolutionary models using an embedded scripting language</p>
</li>
<li>
<p>Allows modeling of spatial and ecological dynamics</p>
</li>
<li>
<p>Provides high flexibility and extensibility for user-defined scenarios</p>
</li>
<li>
<p>Available on GitHub as an open-source project</p>
</li>
</ul><h3>msprime: Ancestry and Mutation Simulator</h3><p>msprime is an efficient, <strong>open-source</strong> tool that simulates ancestry and mutations using a coalescent framework. It is known for its high-speed performance and low memory requirements, making it a popular choice for large-scale genomic simulations.</p><p><strong>Key Features of msprime:</strong></p><ul>
<li>
<p>Implements coalescent simulations for ancestry modeling</p>
</li>
<li>
<p>Efficiently simulates large population histories</p>
</li>
<li>
<p>Supports the addition of mutations to genealogies</p>
</li>
<li>
<p>Developed using an open-source community model</p>
</li>
<li>
<p>Often faster and more memory-efficient than alternative simulators</p>
</li>
</ul><h2>Using SLiM and msprime with slendr</h2><p>Both SLiM and msprime can be integrated with <strong>slendr</strong>, a framework that facilitates structured population genetic simulations. This integration allows for seamless comparison of simulation outputs.</p><h3>How They Work Together:</h3><ul>
<li>
<p>SLiM and msprime simulations can be analyzed within slendr.</p>
</li>
<li>
<p>The <strong>ts_read()</strong> function in slendr enables loading and comparing tree sequence outputs from both simulators.</p>
</li>
<li>
<p>This integration allows researchers to validate simulation results and gain deeper insights into evolutionary processes.</p>
</li>
</ul><h2>Performance Considerations</h2><p>While SLiM offers powerful forward simulations with extensive customization, msprime is often preferred for its <strong>speed and memory efficiency</strong> when simulating ancestry and mutations. The choice between the two depends on the research goals:</p><ul>
<li>
<p><strong>For detailed evolutionary modeling with selection and recombination:</strong> Use SLiM.</p>
</li>
<li>
<p><strong>For large-scale coalescent simulations with mutations:</strong> Use msprime.</p>
</li>
<li>
<p><strong>For comparing different simulation models and their outputs:</strong> Use slendr to integrate SLiM and msprime results.</p>
</li>
</ul><h2>Conclusion</h2><p>SLiM and msprime are valuable tools for genome simulation, each serving distinct but complementary purposes in population genetics research. By leveraging the strengths of both simulators with slendr, researchers can conduct robust and efficient evolutionary simulations, enhancing our understanding of genetic diversity and adaptation.</p><p>For more information, check out the official GitHub repositories for <strong>SLiM</strong> and <strong>msprime</strong>, and explore the <strong>slendr</strong> framework for streamlined simulation workflow</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10262/research-fellow-phd-candidate-in-computational-biology-%E2%80%93-2-positions</guid>
  <pubDate>Fri, 25 Apr 2014 20:19:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research fellow (PhD candidate) in computational biology – 2 positions]]></title>
  <description><![CDATA[
<p>At the Department of Informatics two 4-year positions as research fellow are available in the field of computational biology connected to the Computational Biology Unit. The positions are linked to the project “Integrated genomics - linking transcriptional and translational regulation over developmental time” supported by the Bergen Research Foundation</p>

<p>The fate of a cell is ultimately the product of the regulation of its genes. Gene regulation is a coordinated process acting at multiple levels of which transcription and translation are the most prominent. The Valen group is dedicated to the fundamental question of how transcription and translation is integrated to obtain the desired protein abundance. The recent development of high-throughput next generation sequencing techniques to monitor both active translation and transcription has made it possible to study this connection at the genome scale.</p>

<p>This project aims to elucidate the links between regulation of translation and transcription. The applicant will analyze next generation sequencing data and model gene regulation on a genome-wide level to identify the features that affect the translational output of transcripts. The work will be done in close collaboration with experimental scientists who will test the predictions of the computational models.</p>

<p>Additional information on the position can be obtained by contacting Eivind Valen (eivind.valen@ii.uib.no).</p>

<p>The research fellow must take part in the University’s approved PhD program leading to the degree within a time limit of 3 years. Application for admission to the PhD program, including a project plan outline for the training module, will be worked out in collaboration with the research group in question.</p>

<p>In total, the fellowship period is 4 years, 25 % of this will be allocated to teaching and/or administrative duties. The fellowship period may be reduced if the successful applicant has held previous employment as a research fellow or similar.</p>

<p>http://www.jobbnorge.no/en/available-jobs/job/102235/research-fellow-phd-candidate-in-computational-biology-2-positions</p>
]]></description>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10415/bioinformatician-stuck-in-wet-lab</guid>
	<pubDate>Tue, 06 May 2014 12:46:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10415/bioinformatician-stuck-in-wet-lab</link>
	<title><![CDATA[Bioinformatician stuck in wet-lab]]></title>
	<description><![CDATA[<p>This guide is aimed at pet bioinformaticians, and is meant to guide them towards better career development.</p>
<p><strong>1. Make friends with local bioinformatics groups</strong><br> <strong>2. Talk to your computing group</strong><br> <strong>3. Obtain clear expectations</strong><br> <strong>4. Rewrite your job description</strong><br> <strong>5. Papers</strong><br> <strong>6. Attend bioinformatics meetings</strong><br> <strong>7. Try first, ask later</strong></p><p>Address of the bookmark: <a href="http://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/" rel="nofollow">http://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35899/reference-free-prediction-of-rearrangement-breakpoint-reads</guid>
	<pubDate>Thu, 08 Mar 2018 05:05:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35899/reference-free-prediction-of-rearrangement-breakpoint-reads</link>
	<title><![CDATA[Reference-free prediction of rearrangement breakpoint reads]]></title>
	<description><![CDATA[<p><span>lideSort-BPR (&nbsp;</span><span>b</span><span>&nbsp;reak&nbsp;</span><span>p</span><span>&nbsp;oint&nbsp;</span><span>r</span><span>&nbsp;eads) is based on a fast algorithm for all-against-all comparisons of short reads and theoretical analyses of the number of neighboring reads. When applied to a dataset with a sequencing depth of 100&times;, it finds &sim;88% of the breakpoints correctly with no false-positive reads. Moreover, evaluation on a real prostate cancer dataset shows that the proposed method predicts more fusion transcripts correctly than previous approaches, and yet produces fewer false-positive reads. To our knowledge, this is the first method to detect breakpoint reads without using a reference genome.</span></p>
<p><span>https://github.com/ewijaya/slidesort-bpr</span></p><p>Address of the bookmark: <a href="https://code.google.com/archive/p/slidesort-bpr/" rel="nofollow">https://code.google.com/archive/p/slidesort-bpr/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10881/special-project-scientist-%E2%80%93-sorghum-genomics</guid>
  <pubDate>Tue, 20 May 2014 00:34:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Special Project Scientist – Sorghum Genomics]]></title>
  <description><![CDATA[
<p>ICRISAT is seeking applications from Indian Nationals for a Special Project Scientist to work on a sorghum genomics activities related to sequencing/re-sequencing projects utilizing New Generation Sequencing platforms.</p>

<p>The Job detail</p>

<p>    Advancing the SNP-discovery and polymorphism assessment work across several germplasm panels representing global genetic diversity<br />    Population genetic and genomic analyses, testing the hypothesis related to adaptation in multiple geographic regions<br />    Develop SNP assays from large scale GBS and other re-sequencing data for several target traits utilizing available phenotyping data<br />    Combined analyses of genotypic and phenotypic data for discovery of marker-trait associations, and conducting GWAS<br />    Processing, analyzing, and archiving large-scale genomic data sets, assessing data quality, conducting analyses, interpreting findings, and communicating findings to others including preparation of reports, presentations, posters and journal articles<br />    Providing support to MSc and PhD students on topic related to its major core of research<br />    Any other work assigned by the supervisor</p>

<p>The Person:</p>

<p>    PhD in bioinformatics, genetics, computational biology preferably with 1 to 2 years of experience;<br />    familiar with standard bioinformatics tools and scripting languages and emerging and evolving software platforms relevant to bioinformatics and computational biology;<br />    ability to create new analytical pipelines; experience with handling large data sets;<br />    ability to program in at least two of the following: C++, PERL, Python, R, Java.<br />    will use next-generation sequencing technologies to generate marker data for genetic mapping and transcriptome data for expression QTL mapping, and will be responsible for data generation as well as data analysis.</p>

<p>Period and Remuneration: The assignment is for a period of two years, and can be extended for another year depending on performance. ICRISAT pays a very attractive all inclusive lump sum assignment fee payable in Indian Rupees.</p>

<p>How to Apply: Please send your application by email to icrisatjobs@cgiar.org, stating the job title (Special project Scientist-Sorghum Genomics) clearly in the subject column, addressed to the Director, Human Resources and Operations, ICRISAT, Patancheru, Andhra Pradesh 502 324, India, latest by 10 June 2014. The application should include an up-to-date Curriculum Vitae, a short statement of competencies and experience for the position, and the names and addresses (including phone/e-mail) of three referees. Only short-listed candidates will be contacted.</p>

<p>More at: http://www.icrisat.org/careers/Special-Project-Scientist-Sorghum-Genomics.htm</p>
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