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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39469?offset=430</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:44:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</link>
	<title><![CDATA[Qualimap2: Evaluating next generation sequencing alignment data]]></title>
	<description><![CDATA[<p><strong>Qualimap 2</strong><span>&nbsp;is a platform-independent application written in Java and R that provides both a Graphical User Inteface (GUI) and a command-line interface to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.&nbsp;</span><br><br><span>Supported types of experiments include:</span></p>
<ul>
<li>Whole-genome sequencing</li>
<li>Whole-exome sequencing</li>
<li>RNA-seq (speical mode available)</li>
<li>ChIP-seq</li>
</ul><p>Address of the bookmark: <a href="http://qualimap.bioinfo.cipf.es/" rel="nofollow">http://qualimap.bioinfo.cipf.es/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/13842/swabs-to-genomes-a-comprehensive-workflow</guid>
	<pubDate>Sun, 10 Aug 2014 03:01:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/13842/swabs-to-genomes-a-comprehensive-workflow</link>
	<title><![CDATA[Swabs to Genomes: A Comprehensive Workflow]]></title>
	<description><![CDATA[<p>The sequencing, assembly, and basic analysis of microbial genomes, once a painstaking and expensive undertaking, has become almost trivial for research labs with access to standard molecular biology and computational tools. However, there are a wide variety of options available for DNA library preparation and sequencing, and inexperience with bioinformatics can pose a significant barrier to entry for many who may be interested in microbial genomics. The objective of the present study was to design, test, troubleshoot, and publish a simple, comprehensive workflow from the collection of an environmental sample (a swab) to a published microbial genome; empowering even a lab or classroom with limited resources and bioinformatics experience to perform it.</p><p>Address of the bookmark: <a href="https://peerj.com/preprints/453.pdf" rel="nofollow">https://peerj.com/preprints/453.pdf</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38199/pacasus-correction-of-palindromes-in-long-reads-from-pacbio-and-nanopore</guid>
	<pubDate>Mon, 12 Nov 2018 05:26:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38199/pacasus-correction-of-palindromes-in-long-reads-from-pacbio-and-nanopore</link>
	<title><![CDATA[Pacasus: Correction of palindromes in long reads from PacBio and Nanopore]]></title>
	<description><![CDATA[<p><br>Tool for detecting and cleaning PacBio / Nanopore long reads after whole genome amplification. Check the poster from the Revolutionizing Next-Generation Sequencing (2nd edition) conference in the source folder:&nbsp;<a href="https://github.com/swarris/Pacasus/blob/master/vib2017.pdf">https://github.com/swarris/Pacasus/blob/master/vib2017.pdf</a>.</p>
<p>The prepint version is found on&nbsp;<a href="http://www.biorxiv.org/content/early/2017/08/09/173872">http://www.biorxiv.org/content/early/2017/08/09/173872</a></p>
<p>It uses the pyPaSWAS framework for sequence alignment (<a href="https://github.com/swarris/pyPaSWAS">https://github.com/swarris/pyPaSWAS</a>)</p><p>Address of the bookmark: <a href="https://github.com/swarris/Pacasus" rel="nofollow">https://github.com/swarris/Pacasus</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14050/assistant-professor-in-bioinformatics-at-indian-institute-of-technology-delhi</guid>
  <pubDate>Fri, 15 Aug 2014 06:16:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor 	in Bioinformatics at Indian Institute of Technology Delhi]]></title>
  <description><![CDATA[
<p>Indian Institute of Technology Delhi Hauz Khas ,New Delhi – 110016</p>

<p>ROLLING ADVERTISEMENT NO. 01/2014(E-1)<br />ADVERTISEMENT FOR THE POSITIONS OF ASSISTANT PROFESSOR CANDIDATES CAN APPLY ANY TIME DURING THE YEAR.</p>

<p>IIT Delhi invites applications from qualified Indian Nationals, Persons of Indian Origin (PIOs) and Overseas Citizens of India (OCIs) for the following positions in the various Departments/Centres/Schools (in the fields<br />mentioned alongwith them):<br />Post Pay Band Assistant Professor and Assistant Professor (on Contract) Rs.15600-39100 (PB-3) (Minimum pay of Rs.30000/-)+ AGP Rs.8000/-</p>

<p>The following norms will be followed for fixing the basic pay + AGP for Assistant Professors appointed on<br />contract with Ph.D but experience of 3 years or less:-<br />Type Qualification &amp; Experience on the date of joining<br />Assistant Professor (Contract) PB3 (Rs. 15,600-39,100).</p>

<p>MINIMUM QUALIFICATIONS AND EXPERIENCE:<br />Ph.D. with First class at the preceding degree or equivalent in the appropriate branch with very good academic record throughout. A minimum of three years industrial/research/teaching experience, excluding however, the experience gained while Pursuing Ph. D. The candidates should preferably be below<br />35 years of age for male and 38 years for female ( to be relaxed by 5 years in case of persons with physical disability, SC/ST and 3 years in case of OBC-NCL).</p>

<p>Qualified persons include:<br />(a) Indian Nationals,<br />(b) Foreign Nationals who are “Persons of Indian Origin” (PIO) or Overseas<br />Citizens of India (OCI), in whose case, if selected, permission will be sought from Govt. of India<br />before he/she can join IIT Delhi, or<br />(c) Other Foreign Nationals, in whose case, if selected, appointment will be on a contract basis for up to 5 (five) years subject to permission from the Govt. of India before he/she can join IIT Delhi.<br />(d) Institute specifically encourages applicants from SC/ST/OBC category as well as persons<br />with disability to apply for these positions. </p>

<p>AMAR NATH &amp; SHASHI KHOSLA SCHOOL OF INFORMATION TECHNOLOGY:<br />Computational Neuroscience, Medical Applications of Information Technologies, Computational &amp; Systems Biology, Machine to Machine (M2M) Technologies, Embedded Systems &amp; Sensors, Computer Security.<br />KUSUMA SCHOOL OF BIOLOGICAL SCIENCES:<br />In-silico Biology Applications, Systems Biology, Infection Biology, Neurodegeneration. </p>

<p>More at http://www.iitd.ac.in/sites/default/files/jobs/faculty/spl-areas-rolling-advt.pdf</p>

<p>http://www.iitd.ac.in/content/faculty-positions</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</guid>
	<pubDate>Tue, 14 Jan 2020 06:47:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</link>
	<title><![CDATA[Shasta long read assembler]]></title>
	<description><![CDATA[<p>The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;flow cells.</p>
<p>Computational methods used by the Shasta assembler include:</p>
<ul>
<li>Using a&nbsp;<a href="https://en.wikipedia.org/wiki/Run-length_encoding">run-length</a>&nbsp;representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.</li>
<li>Using in some phases of the computation a representation of the read sequence based on&nbsp;<em>markers</em>, a fixed subset of short k-mers (k &asymp; 10).</li>
</ul>
<p>More at&nbsp;<a href="https://chanzuckerberg.github.io/shasta/index.html">https://chanzuckerberg.github.io/shasta/index.html</a></p><p>Address of the bookmark: <a href="https://github.com/chanzuckerberg/shasta" rel="nofollow">https://github.com/chanzuckerberg/shasta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14272/lecturersenior-lecturer-level-bc-in-bioinformatics</guid>
  <pubDate>Fri, 22 Aug 2014 12:45:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Lecturer/Senior Lecturer (Level B/C) in Bioinformatics]]></title>
  <description><![CDATA[
<p>Lecturer/Senior Lecturer (Level B/C) in Synthetic Biology, Research Fellow (Level B) in Synthetic Biology &amp; Lecturer/Senior Lecturer (Level B/C) in Bioinformatics</p>

<p>Apply now Job no: 494553<br />Work type: Continuing full time<br />Vacancy type: External Vacancy, Internal Vacancy<br />Categories: Academic - Teaching and Research</p>

<p>The Faculty of Science is launching a new and innovative branch of biological science at Macquarie University – Synthetic Biology. Synthetic biology combines engineering principles with molecular biological approaches to design and construct biological devices and systems. Recent highlights in this field include the design and synthesis of a functional bacterial genome and a yeast chromosome, and generation of synthetic bacterial cells. The rational synthesis of "designer" organisms yield important insights into how organisms work and has the potential to revolutionise biotechnological applications in areas such as bioenergy and biomanufacturing.</p>

<p>Find more at http://jobs.mq.edu.au/cw/en/job/494553/lecturersenior-lecturer-level-bc-in-synthetic-biology-research-fellow-level-b-in-synthetic-biology-lecturersenior-lecturer-level-bc-in-bioinformatics</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40715/mutatrix-a-population-genome-simulator-which-generates-simulated-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 04:06:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40715/mutatrix-a-population-genome-simulator-which-generates-simulated-genomes</link>
	<title><![CDATA[mutatrix: a population genome simulator which generates simulated genomes.]]></title>
	<description><![CDATA[<p><span>genome simulation across a population with zeta-distributed allele frequency, snps, insertions, deletions, and multi-nucleotide polymorphisms</span></p>
<p><span>More at&nbsp;<a href="https://github.com/ekg/mutatrix">https://github.com/ekg/mutatrix</a></span></p>
<pre>./mutatrix -S sample -P test/ -p 2 -n 10 reference.fasta</pre><p>Address of the bookmark: <a href="https://github.com/ekg/mutatrix" rel="nofollow">https://github.com/ekg/mutatrix</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14758/phd-opportunity-at-universite-de-liege-belgium</guid>
  <pubDate>Mon, 01 Sep 2014 17:16:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[PhD opportunity at Université de Liège - Belgium]]></title>
  <description><![CDATA[
<p>The Bioinformatics and Systems Biology Unit of Université de Liège (Belgium) is looking for a highly motivated master student with programming skills for a PhD thesis project (4 years, fully funded) with the goal of designing computational tools that use literature, genomic and structural data in order to infer regulatory and metabolic networks.  </p>

<p>Applicants are invited to send their resume and a recommendation letter to Prof. Patrick Meyer (more details at   www.biosys.ulg.ac.be )</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44626/meta-transcriptomics-dynamic-world-of-rna-in-diverse-environments</guid>
	<pubDate>Wed, 31 Jul 2024 02:40:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44626/meta-transcriptomics-dynamic-world-of-rna-in-diverse-environments</link>
	<title><![CDATA[Meta-Transcriptomics: Dynamic World of RNA in Diverse Environments]]></title>
	<description><![CDATA[<p>Meta-transcriptomics combines high-throughput sequencing technologies with computational biology to profile the RNA content of a sample. This technique allows researchers to capture a snapshot of gene expression and metabolic activities across diverse microbial communities, such as those found in soil, water, and the human gut.</p><p><strong>Key Components</strong></p><ol>
<li>
<p><strong>Sample Collection</strong>: Meta-transcriptomics begins with the collection of environmental samples. These samples are often complex, containing a wide range of microorganisms.</p>
</li>
<li>
<p><strong>RNA Extraction</strong>: RNA is extracted from the sample, which includes mRNA, rRNA, tRNA, and other non-coding RNAs. This step is crucial as it determines the quality and representativeness of the data.</p>
</li>
<li>
<p><strong>Sequencing</strong>: High-throughput RNA sequencing (RNA-seq) technologies are used to obtain sequences of the RNA transcripts. This step provides a vast amount of data on the RNA molecules present in the sample.</p>
</li>
<li>
<p><strong>Data Analysis</strong>: Computational tools and bioinformatics methods are employed to process and analyze the sequencing data. This involves mapping RNA sequences to reference genomes or transcriptomes, identifying expressed genes, and quantifying their abundance.</p>
</li>
<li>
<p><strong>Functional Annotation</strong>: The functional roles of identified transcripts are inferred based on known gene functions, allowing researchers to understand the metabolic and ecological functions of the microbial community.</p>
</li>
</ol><p><strong>Applications</strong></p><ol>
<li>
<p><strong>Environmental Monitoring</strong>: Meta-transcriptomics can be used to monitor the health and functional status of ecosystems. For example, it can help assess the impact of pollution on microbial communities by revealing changes in gene expression related to stress response and degradation processes.</p>
</li>
<li>
<p><strong>Microbiome Research</strong>: In human health, meta-transcriptomics offers insights into the gut microbiome&rsquo;s functional state. It helps in understanding how microbial communities interact with their host, how they respond to dietary changes, and their role in health and disease.</p>
</li>
<li>
<p><strong>Biotechnology</strong>: The technique can aid in the discovery of novel enzymes and bioactive compounds by profiling microbial communities in extreme environments or industrial processes.</p>
</li>
<li>
<p><strong>Disease Pathogenesis</strong>: By analyzing RNA profiles from disease-associated environments, researchers can uncover pathogen-host interactions and identify potential targets for therapeutic interventions.</p>
</li>
</ol><p><strong>Challenges</strong></p><ol>
<li>
<p><strong>Complexity of Data</strong>: The sheer volume and complexity of data generated by meta-transcriptomics can be overwhelming. Effective data management and advanced computational tools are required to extract meaningful insights.</p>
</li>
<li>
<p><strong>Sampling Bias</strong>: Environmental samples can be heterogeneous, and RNA extraction methods may introduce biases, potentially affecting the accuracy of the results.</p>
</li>
<li>
<p><strong>Reference Databases</strong>: Incomplete or biased reference databases can hinder the accurate functional annotation of transcripts, especially when studying novel or poorly characterized organisms.</p>
</li>
</ol><p><strong>Future Directions</strong></p><p>Meta-transcriptomics is a rapidly evolving field, with ongoing advancements in sequencing technologies and bioinformatics. Future research may focus on improving data integration, developing more comprehensive reference databases, and enhancing our understanding of microbial community dynamics in various environments. As these challenges are addressed, meta-transcriptomics will continue to provide valuable insights into the functional roles of microorganisms and their interactions within ecosystems.</p><p><strong>Conclusion</strong></p><p>Meta-transcriptomics represents a powerful tool for exploring the functional aspects of microbial communities in their natural environments. By capturing a snapshot of gene expression and metabolic activities, this approach offers a deeper understanding of ecological interactions, health implications, and biotechnological potentials. As technology and methodologies advance, meta-transcriptomics is poised to make significant contributions to our knowledge of the microbial world.</p>]]></description>
	<dc:creator>Abhi</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14905/internship-in-computational-biology</guid>
  <pubDate>Thu, 04 Sep 2014 04:19:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship in Computational Biology]]></title>
  <description><![CDATA[
<p>We are looking for a motivated and autonomous intern to study gene expression in hybrid organisms. The student will work on natural hybrids of two or three different species of fungal endosymbionts of grasses. The pupose of this project is to build software allowing us to identify the genomic origin of expressed genes. To do that, the intern will have to analyze expression data (from RNA-seq) to find SNPs on the sequenced mRNAs allowing to identify from which of the parental genome the expressed gene come from. The data will have to be saved in a database using the standard BioSQL schema.</p>

<p>This job will allow the intern to become more familiar with new biological and bioinformatics tools like next generation sequencing, RNA-Seq data analysis and comparative genomics.</p>

<p>To apply for this position, send the following documents (in PDF format) to Dr Pierre-Yves Dupont (email p.y.dupont@massey.ac.nz):</p>

<p>1. A short cover letter.<br />2. A curriculum vitae, with transcript details.<br />3. The names and contact details of two referees willing to provide a confidential letter of recommendation upon request.</p>

<p>Informal enquiries are welcome. Formal applications are due by Sunday 2nd December 2012.<br />Requirements: </p>

<p>This position requires a good understanding of genetic problems, a good command of at least one scripting language (Perl, Python...), a basic knowledge of MySQL or any relational database management system. Knowledge in biological programming libraries (BioPython, BioPerl, BioRuby...), Java, C++ or any compiled language is an asset but not required. Undergraduate or Master degree is required.<br />Contact Information: </p>

<p>Dr. Pierre-Yves Dupont<br />Institute of Molecular BioSciences<br />Massey University<br />Private Bag 11 222<br />Palmerston North 4442<br />NEW ZEALAND</p>

<p>http://massey.genomicus.com/<br />p.y.dupont@massey.ac.nz</p>

<p>Information about the Institute of Molecular BioSciences (http://imbs.massey.ac.nz/) and the Computational Biology Research Group (http://massey.genomicus.com/) is available online. For more information about the position, you can contact Dr Pierre-Yves Dupont (email p.y.dupont@massey.ac.nz).</p>
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