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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27438?offset=930</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/16158/bioinformatics-position-at-irccs-casa-sollievo-della-sofferenza</guid>
  <pubDate>Wed, 10 Sep 2014 14:25:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics position at IRCCS Casa Sollievo della Sofferenza]]></title>
  <description><![CDATA[
<p>The bioinformatics unit at IRCCS Casa Sollievo della Sofferenza - Mendel laboratory in Rome is looking for one young bioinformatician with specific experience and/or interest in the analysis of genomics and transcriptomic data.</p>

<p>The candidate will be mainly in charge of developing research on Gene Expression/SNP Arrays data, NGS whole -exome and -transcriptome datasets and biological networks in the contexts of genetic diseases, innovative therapies and regenerative medicine. Main activities will be: (i) data analysis (short-reads mapping, genomics aberrations discovery and annotation, variants pathogenicity detection); (ii) functional/pathway enrichment analysis; (iii) biological networks analysis (artificial knockout, redundancy and lethality analysis, gene set essentiality); (iv) developing of ad-hoc software solutions/routines on clusters of CPUs and GPUs.</p>

<p>The correct cultural background (training in Biology / Computer Science / Statistics or a mix of the three) and a strong interest in working in high throughput data analysis will be considered at the same level of specific experience in the above-mentioned fields.</p>

<p>Knowledge of molecular modeling and simulation and willingness to learn one or more of these languages: python, perl, R, Java, C++, C# is a golden plus. Good knowledge of Scientific English will be positively evaluated for this position, together with good presentation and teamwork skills.</p>

<p>Candidates should send:<br />• a cover letter explaining the role they would like to undertake within the Center, even if it is not listed in this job adv, stating clearly why they would be a good fit to the proposed role, and what they would bring to the Center in terms of expertise, ideas, talent;<br />• a CV including a list of publications;<br />• List of referees.</p>

<p>A CV with one professional reference, details on educational background and of the biological and/or bioinformatic and/or data analysis skills and experience should be sent by email for a preliminary selection to: Tommaso Mazza t.mazza@css-mendel.it</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43658/uniquekmer-generate-unique-kmers-for-every-contig-in-a-fasta-file</guid>
	<pubDate>Fri, 17 Dec 2021 00:08:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43658/uniquekmer-generate-unique-kmers-for-every-contig-in-a-fasta-file</link>
	<title><![CDATA[UniqueKmer: Generate unique KMERs for every contig in a FASTA file]]></title>
	<description><![CDATA[<p dir="auto">Generate unique k-mers for every contig in a FASTA file.</p>
<p dir="auto">Unique k-mer is consisted of k-mer keys (i.e. ATCGATCCTTAAGG) that are only presented in one contig, but not presented in any other contigs (for both forward and reverse strands).</p>
<p dir="auto">This tool accepts the input of a FASTA file consisting of many contigs, and extract unique k-mers for each contig.</p>
<p dir="auto">The output unique k-mer file and Genome file can be used for fastv:&nbsp;<a href="https://github.com/OpenGene/fastv">https://github.com/OpenGene/fastv</a>, which is an ultra-fast tool to identify and visualize microbial sequences from sequencing data.</p>
<p>https://github.com/OpenGene/UniqueKMER</p><p>Address of the bookmark: <a href="https://github.com/OpenGene/UniqueKMER" rel="nofollow">https://github.com/OpenGene/UniqueKMER</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17187/urdip-bioinformatics-rajrf-vacancies</guid>
  <pubDate>Sat, 20 Sep 2014 20:52:56 -0500</pubDate>
  <link></link>
  <title><![CDATA[URDIP Bioinformatics RA/JRF Vacancies]]></title>
  <description><![CDATA[
<p>CSIR - UNIT FOR RESEARCH AND DEVELOPMENT OF INFORMATION PRODUCTS (CSIR- URDIP)</p>

<p>Adv. No. URDIP/ 6/2014</p>

<p>Opportunity for young Bioinformatics Professionals to make a career in the area of Intellectual Property CSIR has set up a Unit for Research and Development of Information Products (CSIR-URDIP) at Pune to work in the area of scientific informatics. One of the major focus areas of research work at CSIR-URDIP is PATENT INFORMATICS. With the increasing applications of Bioinformatics in the areas of life sciences industry such as Agriculture and Health Care (Diagnostics and Drugs), the output of research in these area is being protected by different forms of Intellectual Property rights. Realizing the importance of IP in the Bioinformatics field, Department of Biotechnology (DBT) has sanctioned a project on “Development, Facilitation and Harvesting of Bioinformatics related Intellectual Property” at CSIR-URDIP.</p>

<p>The project will involve application of Patent Informatics tools and techniques to Bioinformatics (including creation of patent landscapes, preparation of techno-legal reports of patentability, freedom to operate studies) to help protect IPRs and develop and conduct training programmes on IPRs related to Bioinformatics.</p>

<p>CSIR-URDIP invites applications from young Bioinformatics professionals to work on this emerging area which offers challenging opportunities and attractive career possibilities in future.</p>

<p>Position I: Research Associate</p>

<p>No of Positions: One</p>

<p>Consolidated amount Payable: Rs. 22,000/- per month + 20% HRA= Rs.26,400</p>

<p>Qualification:  PhD in Bioinformatics. In exceptional cases, candidature of M. Tech. candidates with First class in Bioinformatics with three years of relevant work experience will also be considered.</p>

<p>Age Limit: 35 years. The age should not exceed the limit indicated as on a closing date of receipt of completed application form.</p>

<p>Upper age limit is relaxable for 5 years for SC/ST, OBC, Physically handicapped and female candidates as per CSIR/Government of India rules.</p>

<p>Position II: Junior Research Fellow</p>

<p>No of Positions: one</p>

<p>Consolidated amount Payable: Rs. 16,000/- + 20% HRA = 19,200</p>

<p>Qualification: M.Sc / BE or equivalent in Bioinformatics with minimum of 55% marks in aggregate Job requirement: Scientific literature and patent search, analysis and Report Writing</p>

<p>Preference: Preference will be given to candidates with knowledge of patents and or 1-2 years of experience + Knowledge of Computers (MS Excel + Word Processing)</p>

<p>Age Limit: 28 years. The age should not exceed the limit indicated as on a closing date of receipt of completed application form.</p>

<p>For details please visit our website (www.urdip.res.in/careers) for further details and apply online by 30th September, 2014.</p>

<p>Advertisement: http://www.urdip.res.in/download/Advt6_2014.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43799/kast</guid>
	<pubDate>Wed, 23 Feb 2022 08:28:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43799/kast</link>
	<title><![CDATA[KAST]]></title>
	<description><![CDATA[<p><span>Perform Alignment-free k-tuple frequency comparisons from sequences. This can be in the form of two input files (e.g. a reference and a query) or a single file for pairwise comparisons to be made.</span></p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/KAST" rel="nofollow">https://github.com/martinjvickers/KAST</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17176/arvados</guid>
	<pubDate>Sat, 20 Sep 2014 16:54:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17176/arvados</link>
	<title><![CDATA[Arvados]]></title>
	<description><![CDATA[<p>Arvados is a free and open&nbsp;source bioinformatics&nbsp;platform for genomic and&nbsp;biomedical data. User can&nbsp;Store | Organize | Compute | Share the data for free.&nbsp;</p>
<p><img src="https://arvados.org/images/dax.png" width="400" height="535" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://arvados.org/" rel="nofollow">https://arvados.org/</a></p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
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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/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/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>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45240/pg2-making-pangenome-graphs-easier-to-understand</guid>
	<pubDate>Tue, 18 Aug 2026 04:38:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45240/pg2-making-pangenome-graphs-easier-to-understand</link>
	<title><![CDATA[PG2: Making Pangenome Graphs Easier to Understand]]></title>
	<description><![CDATA[<p>Genomics is moving beyond the traditional approach of studying DNA using a single reference genome. Today, researchers are increasingly using pangenomes, which represent genetic information from multiple genomes and capture a much broader range of genetic diversity.</p><p>However, pangenome graphs can be highly complex, making them difficult to visualize and interpret. A recent study published in BMC Bioinformatics introduces PG2 (PanGenoGrapher), an open-source, web-based tool designed to address this challenge.&nbsp;The source code and user guide are openly available on GitHub at https://github.com/iVis-at-Bilkent/pangenographer. A publicly accessible sample deployment is hosted at http://pg2.cs.bilkent.edu.tr. In addition, a demonstration video illustrating the primary use cases of PG2 is available at https://www.youtube.com/watch?v=yCd7-aGY6CQ.</p><p>PG2 combines advanced graph-layout algorithms with an interactive visualization platform. It allows researchers to explore genomic paths, identify variations, and examine relationships between different parts of a pangenome graph more easily.</p><p>This is important because visualization can play a major role in bioinformatics. When complex genomic information is presented clearly, researchers can more easily identify patterns, understand genetic variation, and generate new biological insights.</p><p>The development of PG2 represents a step toward making pangenome analysis more accessible and intuitive. As genomic datasets continue to grow and graph-based representations become more common, tools like PG2 can help researchers navigate this increasing complexity.</p><p>Ultimately, PG2 demonstrates how combining genomics, graph algorithms, and interactive visualization can make sophisticated biological data easier to understand and analyze.</p><p>Reference: Solun, G. K., Dogrusoz, U., Bing&ouml;l, Z., &amp; Alkan, C. (2026). PG2: algorithms and a web-based tool for effective layout and visual analysis of pangenome graphs. BMC Bioinformatics. DOI: 10.1186/s12859-026-06555-4.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18819/jrfsrf-at-jawaharlal-nehru-institute-ofadvanced-studies-jnias-hyderabad</guid>
  <pubDate>Fri, 31 Oct 2014 08:48:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF at Jawaharlal Nehru Institute ofAdvanced Studies (JNIAS), Hyderabad]]></title>
  <description><![CDATA[
<p>Applications for Academic Projects in Biotechnology, Bioinformatics, Environmental Sciences and Computer Science &amp; Engineering</p>

<p>About JNIAS<br />Jawaharlal Nehru Institute of Advanced Studies (JNIAS), Hyderabad has been established by Dr. D. Swaminadhan Research Foundation (DSRF), Hyderabad as a Research and Educational Institution with a view to contribute in developing advanced technologies and build „core competence‟ in specific areas. The activities of JNIAS involves: Education, Research Training and Innovations in the fields of Sciences, Technologies, Humanities and Social Sciences. It aims to blossom into an Advanced Institute of education and research with a reservoir of expertise and experience in the relevant fields and the necessary capability to harness multi-disciplinary research and studies. JNIAS has been recognized as an Advanced Research Institute by Jawaharlal Nehru Technological University Hyderabad (JNTUH), Hyderabad and Jawaharlal Nehru Technological University Anantapur (JNTUA), for offering Ph.D., P.G M.Phil, P.G Diploma and Training Programmes in Sciences and Engineering &amp; Technology.</p>

<p>Jawaharlal Nehru Architecture and Fine Arts University (JNAFAU) Hyderabad also recognized JNIAS for offering UG, PG degree in Architecture.</p>

<p>Projects &amp; Facilities</p>

<p>JNIAS offers wide range of projects:</p>

<p>Biotechnology area:</p>

<p>Molecular Biology<br />Microbiology<br />Nanotechnology<br />Bioinformatics (Schrodinger Software)<br />In Silico studies &amp; Drug Designing<br />Sequence analysis<br />Protein structure function studies</p>

<p>Registration<br />Tuition Fees: Interested students need to pay the following tuition fees:<br />1. Six Month’s Project: Rs. 20,000/-<br />2. Four Month’s Project: Rs. 15,000/-<br />3. Three Month’s Project: Rs. 10,000/-<br />4. One Month - Hands on Training : Rs. 8,000/-</p>

<p>For enquires call:<br />91-7893203414 (Biotechnology), 91-9949582263 (Environmental Sciences) 91-8977369305 (Computer Science)</p>

<p>Interested student may download the application from the website (www.jnias.in) and send the hard copy of the completed application forms and Curriculum Vitae along with the Demand Draft drawn on any nationalized Banks in favor of “The Registrar, JNIAS, Secunderabad”. Application forms can be sent through email to academicprojects@jnias.in</p>

<p>Address<br />Jawaharlal Nehru Institute of Advanced Studies (JNIAS)<br />6th Floor, Buddha Bhavan, M.G Road,<br />Secunderabad - 500 003<br />Andhra Pradesh, India<br />Tele/Fax: 040- 27541551; 27541553<br />Mobile: 08885541554<br />Web site: www.jnias.in</p>

<p>Brochure : https://drive.google.com/file/d/0B3zPwhgA-u-nU0dyMFd2OWcxNUpSTWNYc0xDSGs5UDI4UDNB/view?usp=sharing</p>
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