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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27035?offset=1220</link>
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	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</guid>
	<pubDate>Mon, 17 Aug 2020 05:25:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</link>
	<title><![CDATA[SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins]]></title>
	<description><![CDATA[<p>SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:</p>
<ol>
<li>Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome</li>
<li>Co-assembly of a large number of metagenomes via merging of individual metagenomes</li>
<li>Includes binning and bin checking, for retrieving individual genomes</li>
<li>The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.</li>
<li>Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.</li>
<li>Metatranscriptomic support via mapping of cDNA reads against reference metagenomes</li>
</ol><p>Address of the bookmark: <a href="https://github.com/jtamames/SqueezeMeta" rel="nofollow">https://github.com/jtamames/SqueezeMeta</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12896/inspire-faculty-scheme-a-component-of-%E2%80%9Cassured-opportunity-for-research-career-aorc%E2%80%9D-under-inspire</guid>
  <pubDate>Sat, 19 Jul 2014 14:59:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.]]></title>
  <description><![CDATA[
<p>Ministry of Science and Technology, Department of Science and Technology</p>

<p>7th ADVERTISEMENT – 2014 (2)</p>

<p>INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.</p>

<p>The Department of Science and Technology, Government of India, has launched the “Innovation in Science Pursuit for Inspired Research (INSPIRE)” [http://www.inspire-dst.gov.in] program in 2008.</p>

<p>The program aims to attract talent for study of science and careers with research. INSPIRE includes many components. The importance of Assured Career Opportunity in R&amp;D sector has been recognized.</p>

<p>INSPIRE Faculty Scheme opens up an “Assured Opportunity for Research Career (AORC)” for young researchers in the age group of 27-32 years. It offers a contractual research awards to young achievers and opportunity for independent research in the near term and emerge as a future leader in the long term.</p>

<p>Eligibility</p>

<p>Essential Indian citizens and people of Indian origin including NRI/PIO status with PhD (in science, mathematics, engineering, pharmacy, medicine, and agriculture related subjects) from any recognized university in the world,</p>

<p>Those who have submitted their PhD Theses and are awaiting award of the degree are also<br />eligible. However, the award will be conveyed only after confirmation of the awarding the<br />PhD degree.</p>

<p>The upper age limit as on 1st July 2014 should be 32 years for considering support for a<br />period of 5 years. However, for SC and ST candidates, upper age limit will be 35 years.</p>

<p>Publication(s) in highly reputed Journals demonstrating research potential of the candidate.</p>

<p>Desirable</p>

<p>Candidates who are within top 1% at the School Leaving Examination, IIT-JEE rank, 1st Rank Holder either in graduation or post-graduation level university examination (which are used presently for identifying INSPIRE Scholars at under-graduate level and INSPIRE Fellows for doctoral degree)</p>

<p>More at http://www.inspire-dst.gov.in/faculty_scheme.html</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11494/postdoc-position-at-centre-mediterraneen-de-medecine-moleculaire-nice-france</guid>
  <pubDate>Wed, 04 Jun 2014 07:20:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position at Centre Méditerranéen de Médecine Moléculaire - Nice - France]]></title>
  <description><![CDATA[
<p>The research group of Dr. Michele Trabucchi at the Centre Méditerranéen de Médecine Moléculaire (C3M) at INSERM U1065 (University of Nice Sophia-Antipolis, France) is seeking candidates for a Postdoctoral fellow position to start on October 2014 for 3 years funded by FRM (Fondation pour la Recherche Médicale).<br />The broad interest of the lab is in understanding the expression control and function of small RNAs in activated myeloid cells (visit our webpage to check research interests and publications of the group : http://www.unice.fr/c3m/EN/Equipe10.html ). </p>

<p>The work will focus on the functional studies of small RNAs by using next-generation sequencing approaches.<br /> <br />Candidates should hold a Ph.D. degree and have strong background in bioinformatics.<br />The University of Nice Sophia-Antipolis provides a wide range of facilities and training essential for biomedical research.</p>

<p>Interested applicants should send a PDF with a cover letter stating research interests and qualifications, an updated CV, a summary of previous research experience and contact information for two references to Michele Trabucchi ( mtrabucchi@unice.fr )</p>

<p>Homepage: http://www.unice.fr/c3m/EN/Equipe10.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</guid>
	<pubDate>Thu, 09 Mar 2023 02:56:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</link>
	<title><![CDATA[Steps to find palindrome in genomes !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Palindromes are sequences of nucleotides that read the same backward as forward. They can be present in genomes and have various biological functions. Here are some methods for discovering palindromes in genomes:</p><ol>
<li>
<p>Direct sequence search: One of the simplest ways to discover palindromes is to search the genome sequence directly for palindromic sequences using pattern matching tools, such as regular expressions or string algorithms. This approach can be useful for discovering simple palindromes, but may miss more complex palindromic structures.</p>
</li>
<li>
<p>Dot plot analysis: Dot plot analysis is a graphical method that can be used to identify palindromic regions in a genome. It involves plotting the genome sequence against itself and examining the diagonal patterns that emerge. Palindromic regions will appear as symmetrical patterns along the diagonal.</p>
</li>
<li>
<p>Restriction enzyme analysis: Some restriction enzymes, such as EcoRI and HindIII, recognize palindromic sequences and cleave DNA at these sites. By digesting the genome with these enzymes and examining the resulting fragments, palindromic regions can be identified.</p>
</li>
<li>
<p>Next-generation sequencing: High-throughput sequencing technologies, such as PacBio and Oxford Nanopore, can generate long reads that can span entire palindromic regions. By mapping these reads to the genome, palindromic regions can be identified and characterized.</p>
</li>
<li>
<p>Comparative genomics: Comparing the genomes of related species can also reveal palindromic regions that are conserved across evolutionarily divergent lineages. This approach can help identify functional palindromes that are under selective pressure.</p>
</li>
</ol><p>Overall, the discovery of palindromic sequences in genomes can be accomplished using a variety of methods, each with their own advantages and limitations. A combination of these methods can provide a comprehensive understanding of the palindromic landscape of a genome.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</guid>
	<pubDate>Sun, 08 Jun 2014 10:06:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</link>
	<title><![CDATA[Ten recommendations for creating usable bioinformatics command line software]]></title>
	<description><![CDATA[<p><span>Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author&rsquo;s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user&rsquo;s time, and improve the quality of scientific analyses.</span></p><p>Address of the bookmark: <a href="http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer" rel="nofollow">http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44593/bear-better-emulation-for-artificial-reads</guid>
	<pubDate>Sat, 06 Jul 2024 04:27:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44593/bear-better-emulation-for-artificial-reads</link>
	<title><![CDATA[BEAR: Better Emulation for Artificial Reads]]></title>
	<description><![CDATA[<p dir="auto">Created by Stephen Johnson, Brett Trost, Dr. Jeffrey R. Long, Dr. Anthony Kusalik University of Saskatchewan, Department of Computer Science</p>
<p dir="auto">BEAR is intended to be an easy-to-use collection of scripts for generating simulated WGS metagenomic reads with read lengths, quality scores, error profiles, and species abundances derived from real user-supplied WGS data.</p><p>Address of the bookmark: <a href="https://github.com/sej917/BEAR" rel="nofollow">https://github.com/sej917/BEAR</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12567/workshop-on-molecular-modeling-and-dynamics-simulation-analyses</guid>
  <pubDate>Fri, 04 Jul 2014 13:38:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[Workshop On Molecular Modeling and Dynamics Simulation Analyses]]></title>
  <description><![CDATA[
<p>Workshop On Molecular Modeling and Dynamics Simulation Analyses</p>

<p>August1-2, 2014</p>

<p>Organised By</p>

<p>Centre of Excellence in Bioinformatics<br />Bioinformatics Infrastructure Facility<br />Department of Biochemistry<br />University of Lucknow<br />Lucknow-226007</p>

<p>Course Contents</p>

<p>Molecular Modeling<br /> Homology Modeling<br />Molecular Docking<br />Post-structural Analyses</p>

<p>Molecular Dynamics (MD)<br />Simulation<br />Linux Introduction<br />Gromacs Installation</p>

<p>MD Simulation of Protein ligand complex<br />Analyses of MD<br />Trajectories<br />Visualization of Dynamic<br />complexes</p>

<p>Important Dates</p>

<p>Registration Begins June 25, 2014<br />Registration Closes July 25, 2014</p>

<p>Brochure : www.lkouniv.ac.in/conference/Brochure_August,%202014.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/12883/breaking-chromosomes-to-study-cancer</guid>
	<pubDate>Fri, 18 Jul 2014 05:42:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/12883/breaking-chromosomes-to-study-cancer</link>
	<title><![CDATA[Breaking chromosomes to study cancer !!!]]></title>
	<description><![CDATA[<p>Chromosomes are present in every cell of our body and they contain the information the body needs to develop and function properly. This information is carried in genes that are arranged along the chromosomes. There are usually 46 chromosomes in every cell. These chromosomes come in pairs, one from our mother and one from our father. The chromosomes can be sorted into 23 pairs by looking at them down a microscope.</p><p>Most people who have a balanced translocation have the right amount of chromosome material but it has been rearranged in some way. This may happen if two chromosomes swap pieces (a reciprocal translocation). In other cases two whole chromosomes may become stuck together (a Robertsonian translocation). This page describes what happens when someone has a reciprocal translocation. <br /><br />Reciprocal chromosomal translocations occur following double-strand breaks (DSBs) in DNA when a section of one chromosome is exchanged with that of another, non-homologous chromosome. These exchanges may produce a dysfunctional fusion gene that disrupts cell growth and survival pathways, such as the translocations seen in leukemia and childhood sarcomas. <br /><br />Chromosomal translocations have been well studied in cancer cell lines which are associated with two types of cancer, acute myeloid leukemia and Ewing's sarcoma, but determining how they contribute to cancer development is complicated by additional mutations and altered gene expression profiles in these cultured cells. Now, Juan Carlos Ramirez, head of the Viral Vector Facility at the Fundacion Centro Nacional de Investigaciones Cardiovasculares (CNIC) and his colleagues Raul Torres at CNIC and Sandra Rodriguez-Peralez at the Spanish National Cancer Center (CNIO) in Madrid, Spain have used a new genome editing tool, CRISPR-Cas9, to induce chromosomal translocations for the first time in a human cell line and in primary cells. The study's authors conclude by stating that the use of this technology will allow for the clarification of how and why chromosomal translocation occurs, which without doubt will allow new anti-cancer therapeutic strategies to be tackled.</p><p>Using RNA-Guided Endonuclease (RGEN) technology or CRISPR/Cas9 genome engineering technology, CNIO and CNIC researchers have shown that it is possible to obtain such chromosomal translocations. The CRISPR-Cas9 system is extremely simple to introduce a cut at the desired locus, easier to design, and cheaper than many other systems. Using the CRISPR-Cas9 system, Ramirez and his colleagues reproduced the translocations observed in Ewing&rsquo;s Sarcoma (ES) and Acute Myeloid Leukemia (AML) patient cell lines in HEK293 cells and also generated the ES translocation in human mesenchymal stem cells and the AML translocation in umbilical cord blood cells.</p><p>By focusing on chromosomal translocation without the confounding characteristics of established cell lines, these new cells lines should help answer the fundamental question of what causes a cell to become cancerous. Ramirez and his team now look forward to modeling other chromosome translocations in a variety of cell types.</p><p>Reference:</p><p>http://en.wikipedia.org/wiki/Chromosomal_translocation</p><p>http://www.nature.com/ncomms/2014/140603/ncomms4964/abs/ncomms4964.html<br /><br /></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12940/ra-at-iiser-kolkata-computational-biologybioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 06:24:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA at IISER Kolkata Computational Biology/Bioinformatics]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for research associate (post-doc; Rs. 22000-32000)/research fellow (16000-18000)/project assistant (Rs. 10000-14000) positions in the Department of Biological Sciences, Indian Institute for Science Education and Research Kolkata in the extramural project. Condition to satisfactory performance, the positions is for a period of upto 2 years (or funding of the project).</p>

<p>Brief description: We are looking for suitable candidates in the area o computational biology/bioinformatics/genomics or related field for next-generation sequencing (NGS) data analysis for small-RNAs, RNA-Seq and targeted resequencing of plants and associated organisms. We are an interdisciplinary group where projects equally involve bioinformatics and systems biology (specially microarrays and next-generation sequencing (NGS) data analysis and its use), along with plant molecular biology, genetic engineering, field biology, and analytical plant chemistry for understanding response of plants to biotic stresses.</p>

<p>Essential qualification: MSc/BTech/MTech/PhD (or other suitable qualification) in disciplines preferable to bioinformatics, computational biology, computer application (or equivalent)/ ‘Advance Post-Graduate Diploma in Bioinformatics’. Proficiency in programming languages (such as Perl, C++) and/or statistics (proficient in R for example) is compulsory.</p>

<p>Desirable qualification: Experience in the field of genomics e.g. microarray analysis, NGS, genome annotation, database development and management, software development, systems and network biology (or related fields) will be preferred.</p>

<p>Application process: Applications should contain CV along with brief description (maximum 1 page) of research conducted (highlighting skills and experience) till now. Applications should be sent by e-mail to Shree Prakash Pandey, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur Campus, WB, India within 14 days of this advertisement.</p>

<p>E-mail: sppiiserkol@gmail.com, sppandey@iiserkol.ac.in</p>

<p>Advertisement:</p>

<p>http://www.iiserkol.ac.in/announcements/adverts/671-advt_ra_shree_prakash_july_2014</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</guid>
	<pubDate>Sun, 27 Jul 2014 20:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</link>
	<title><![CDATA[You and your friend have similar DNA !!!]]></title>
	<description><![CDATA[<p>New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS&nbsp;http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.</p><div style="text-align: center;"><img src="http://i.kinja-img.com/gawker-media/image/upload/s--CwLwHa43--/18fbmlokxcmqcjpg.jpg" alt="image" width="300" height="271" style="border: 0px; border: 0px;"></div><p>Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes &mdash; a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.&nbsp;</p><p>The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.</p><p>Reference:</p><p>http://www.pnas.org/content/111/Supplement_3/10796.full</p><p>Image : http://i.kinja-img.com</p>]]></description>
	<dc:creator>Jit</dc:creator>
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