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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31087?offset=850</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30928/jrf-bioinformatics-job-vacancies-in-tezpur-university</guid>
  <pubDate>Tue, 14 Feb 2017 16:40:26 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics job vacancies in Tezpur University]]></title>
  <description><![CDATA[
<p>Memo No. DoRD/CSE/SSS/20-295/112-A Date: 01/02/2017</p>

<p>Project Title : Integrating genome scale metabolic analysis of model plant pathogen Ralstonia solanacearum with RNAseq and fluxomics</p>

<p>Essential qualification : M.Tech. in CSE/IT (With specialization in Computational Biology/Bioinformatics) or M.Sc. in Bioinformatics/Biosciences/Molecular Biology Biotechnology preferably with NET/GATE/BET. Candidates should have minimum 55 % mark both in 10th and 10+2 Science examinations and mathematics at 10+2 Science. Desirable: Preference will be given to the candidates having experience in computational analysis of genome sequences or similar projects.</p>

<p>No. of Post : 01</p>

<p>Remuneration : Rs. 25,000/- for the 1st two years and Rs. 28,000/- for the 3rd year for SRF and applicable to the candidate having post graduate degree in Basic Science with NET/GATE/BET qualification or post graduate degree in professional course. Rs. 12,000/- for the 1st two years and Rs. 14,000/- for the 3 rd year for SRF, </p>

<p>Age : 28 years</p>

<p>Duration : Three (03) years or till completion of the project or until further order, whichever is earlier.</p>

<p>Hiring Process : Walk - In<br />Job Role: Research/JRF/SRF</p>

<p>Walk-in-interview will be held on 17th February, 2017, 11.15 a.m. at the office of the Head, Department of Computer Science and Engineering, Tezpur University.</p>

<p>Interested candidates may appear before the interview board with original documents from 10th standard onwards and photocopies of mark sheets, certificates, testimonials, caste certificate (if applicable), experience certificate certificates of NET/GATE/BET or similar examination qualifications, any other testimonials and a copy of recent curriculum vitae (CV) on the day of interview.</p>

<p>More at http://www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-SSS-20-295-112-A.pdf</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32227/postdoctoral-research-position-in-bioinformatics-in-milan</guid>
  <pubDate>Thu, 20 Apr 2017 12:53:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Research Position in Bioinformatics in Milan]]></title>
  <description><![CDATA[
<p>The lab of Immunobiology of Neurological Disorders has a main interest in the biological processes associated with multiple sclerosis, an inflammatory disorder of the central nervous system. The projects of interest for this application involve research on translational bioinformatics in complex human neurological disorders.</p>

<p>You have a  PhD in Computational Science, Bioinformatics,  or equivalent, and expertise in analysis and modeling of human RNA-seq data, statistics, data mining and machine learning. Excellent communication skills in English (written and oral) is a must. Flexibility and willingness to work across multiple projects and technologies in a rapidly evolving scientific context is required.<br />Salary will depend on qualification and experience. Starting date: immediate.</p>

<p>Interested candidates should send to farina.cinthia@hsr.it:</p>

<p>1. CV (please show evidences of relevant titles, projects, courses, references, etc.)           <br />2. One page with a list of research topics (i.e. ongoing projects)     <br />3. earliest availability</p>

<p>4. 2-3 contact names</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37221/asplice-a-scalable-and-memory-efficient-algorithm-for-de-novo-transcriptome-assembly</guid>
	<pubDate>Tue, 03 Jul 2018 04:09:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37221/asplice-a-scalable-and-memory-efficient-algorithm-for-de-novo-transcriptome-assembly</link>
	<title><![CDATA[ASplice: a scalable and memory-efficient algorithm for de novo transcriptome assembly]]></title>
	<description><![CDATA[With increased availability of de novo assembly algorithms, it is feasible to study entire transcriptomes of non-model organisms. While algorithms are available that are specifically designed for performing transcriptome assembly from high-throughput sequencing data, they are very memory-intensive, limiting their applications to small data sets with few libraries.

Texas A&amp;M University researchers develop a transcriptome assembly algorithm that recovers alternatively spliced isoforms and expression levels while utilizing as many RNA-Seq libraries as possible that contain hundreds of gigabases of data. New techniques are developed so that computations can be performed on a computing cluster with moderate amount of physical memory.

Availability – A software program that implements the algorithm is available at: http://faculty.cse.tamu.edu/shsze/asplice.

Sze SH, Pimsler ML, Tomberlin JK, Jones CD, Tarone AM. (2017) A scalable and memory-efficient algorithm for de novo transcriptome assembly of non-model organisms. BMC Genomics 18(Suppl 4):387.<p>Address of the bookmark: <a href="http://faculty.cse.tamu.edu/shsze/asplice/" rel="nofollow">http://faculty.cse.tamu.edu/shsze/asplice/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/31258/bioinformatics-walk-in-interview-at-tezpur-university</guid>
  <pubDate>Thu, 02 Mar 2017 04:24:46 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics walk-in-interview at Tezpur University]]></title>
  <description><![CDATA[
<p>A walk-in-interview will be held on 09 March, 2017, 11.15 a.m. at the office of the Head, Department of Computer Science and Engineering, Tezpur University for one (01) temporary position of Junior Research Fellow (JRF) in the DBT, Govt. of India sponsored project entitled “Integrating genome scale metabolic analysis of model plant pathogen Ralstonia solanacearum with RNAseq and fluxomics” under Dr. Siddhartha Sankar Satapathy (ssankar@tezu.ernet.in), Associate Professor, Department of Computer Science and Engineering, Tezpur University.<br /> <br />Interested candidates may appear before the interview board with original documents from 10th standard onwards and photocopies of mark sheets, certificates, testimonials, caste certificate (if applicable), experience certificate certificates of NET/GATE/BET or similar examination qualifications, any other testimonials and a copy of recent curriculum vitae (CV) on the day of interview.<br /> <br />Essential qualification: M.Tech. in CSE/IT (With specialization in Computational Biology/Bioinformatics) or M.Sc. in Bioinformatics/Biosciences/Molecular Biology Biotechnology preferably with NET/GATE/BET.<br /> <br />Candidates should have minimum 55 % mark both in 10th and 10+2 Science examinations and mathematics at 10+2 Science.<br /> <br />Desirable: Preference will be given to the candidates having experience in computational analysis of genome sequences or similar projects.<br /> <br />Remuneration: Rs. 25,000/- (Rupees twenty five thousand) only + HRA as admissible per month for the 1st two years and Rs. 28,000/- (Rupees twenty eight thousand) only + HRA as admissible per month for the 3rd year for SRF and applicable to the candidate having post graduate degree in Basic Science with NET/GATE/BET qualification or post graduate degree in professional course. Rs. 12,000/- (Rupees twelve thousand) only + HRA as admissible per month for the 1st two years and Rs. 14,000/- (Rupees fourteen thousand) only + HRA as admissible per month for the 3 rd year for SRF, for the candidate without NET/GATE/BET qualification. HRA will not be provided if campus accommodation is availed.<br /> <br />Age: Candidate shall not be more than 28 years of age on the date of interview. Upper age limit may be relaxed up to 5 years in the case of candidate belonging to SC/ST/ OBC/Women/Differently abled.<br /> <br />Duration: Three (03) years or till completion of the project or until further order, whichever is earlier.<br /> <br />N.B. No TA/DA will be paid to the candidates for attending the interview. For further details please contact: Dr. S. S. Satapathy Associate Professor Department of Computer Science and Engineering Tezpur University, Napaam-784028 Email: ssankar@tezu.ernet.in Contact no.: +91-9435979648<br /> <br />More Info:  www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-SSS-20-295-188-A.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</guid>
	<pubDate>Sun, 02 Apr 2017 14:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</link>
	<title><![CDATA[Fools guide]]></title>
	<description><![CDATA[<p><span>This website and accompaning documents are intended as a tool to help researchers dealing with non-model organisms acquire and process transcriptomic high-throughput sequencing data without having to learn extensive bioinformatics skills. It covers all steps from tissue collection, sample preparation and computer setup, through addressing biological questions with gene expression and SNP data.</span></p>
<p>http://sfg.stanford.edu/denovo.html</p>
<p>http://sfg.stanford.edu/sequencing.html</p>
<p>http://sfg.stanford.edu/BLAST.html</p>
<p>http://sfg.stanford.edu/denovo.html&nbsp;</p><p>Address of the bookmark: <a href="http://sfg.stanford.edu/guide.html" rel="nofollow">http://sfg.stanford.edu/guide.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32374/ra-bioinformatics-at-jnu-new-delhi-india</guid>
  <pubDate>Thu, 27 Apr 2017 03:29:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at JNU, New Delhi, INDIA]]></title>
  <description><![CDATA[
<p>School of Computational &amp; Integrative Sciences<br />Jawaharlal Nehru University<br />New Delhi-110067, INDIA</p>

<p>Date: April 24th. 2017	Last Date: May 6th 2017<br />PROJECT ID: 632</p>

<p>The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project jointly running with IIIT-Hyderabad &amp; JNU, entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067.<br />NB: For all the posts, preference will be given to candidates with a good knowledge of Python and/or R in UNIX platform , knowledge of JAVA will also get a special consideration.</p>

<p>1.	RA / Research Associate (Metabolic engineering/Computational Biologist)</p>

<p>Salary: Rs. 36000/- + HRA</p>

<p>Vacancy: 1</p>

<p>Essential Qualifications: PhD in Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/Analysis of Network Biology/Chemoinformatics/Computational Biology related Software development. Published paper in the field is a must to prove the experience. Special consideration will be given if have experience in Industry, teaching &amp; product development.</p>

<p>Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , collaborating with industry , preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.</p>

<p>2.	Project SRF (Network model building/Systems biology integration)</p>

<p>Salary*: Rs.18000/- + HRA</p>

<p>Vacancy: 1</p>

<p>Essential Qualifications: M.Tech in Computational Biology with project experience or Masters / B.Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Mathematical Model building using Computational Biology tools &amp; related Database / Network analysis etc. For M.Sc/B.Tech, Published paper in peer-reviewed Journal whereas for M.Tech, the degree obtained in computational biology is a must.</p>

<p>Desired Skills: Will be expected to manage ongoing research activities in LIMS, interact with LIMS group, build network model using data compiled by experimentalist, prepare and file reports and associated project work etc. Familiarity with plant systems biology and genomics /metabolite resources related to plant metabolomics is desirable.</p>

<p>More at http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38792/nxrepair-error-correction-in-de-novo-assemblies-using-nextera-mate-pair-reads</guid>
	<pubDate>Thu, 24 Jan 2019 10:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38792/nxrepair-error-correction-in-de-novo-assemblies-using-nextera-mate-pair-reads</link>
	<title><![CDATA[NxRepair: error correction in de novo assemblies using Nextera Mate Pair Reads]]></title>
	<description><![CDATA[<p>NxRepair is a python module that automatically detects large structural errors in de novo assemblies using Nextera mate pair reads. The decector will break a contig at the site of an identified misassembly and will generate a new fasta file containing both the corrected contigs and the correct, unaffected contigs.</p>
<p>https://nxrepair.readthedocs.io/en/latest/tutorial.html</p>
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<pre>nxrepair aligned_matepairs.bam assemblyfasta.fasta error_locations.csv new_fasta.fasta</pre>
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<div>&nbsp;</div><p>Address of the bookmark: <a href="https://github.com/rebeccaroisin/nxrepair" rel="nofollow">https://github.com/rebeccaroisin/nxrepair</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/32496/bioinformatician-at-23andme</guid>
  <pubDate>Sat, 06 May 2017 17:57:39 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatician at 23andMe]]></title>
  <description><![CDATA[
<p>23andMe’s mission is to help people access, understand, and benefit<br />from the human genome. We are a group of passionate individuals excited<br />to push the boundaries of what’s possible to help turn genetic insight<br />into better health and personal understanding.</p>

<p>Our Research Team prides itself on driving cutting edge, industrial-scale<br />science to make an impact that belies the team’s size, in an environment<br />and culture that fosters creativity, innovation, collaboration, and fun.</p>

<p>More than 80% of our customers consent to participate in research, and as<br />a result of their participation, we have one of the largest recontactable,<br />genotyped, and phenotyped research cohorts in the world. The scope and<br />breadth of our vision means that most of the methods and tools necessary<br />to unlock the potential of this unique resource for discovery have yet<br />to be developed.</p>

<p>Our science has garnered the respect of many members of the<br />broader scientific community. For a list of our publications, see<br />www.23andme.com/publications/for-scientists/.</p>

<p>Join us! Visit our Careers page (www.23andMe.com/careers) to learn more<br />about these open positions:</p>

<p>•	Scientist, Research Communications<br />•	Bioinformaticist<br />•	Computational Biologist, Ancestry R&amp;D<br />•	Scientist/Senior Scientist, Statistical Genetics<br />•	Scientist/Senior Scientist, Survey Methodology<br />•	Scientist/Senior Scientist, Health R&amp;D<br />•	Senior Computational Biologist<br />•	Biostatistician</p>

<p>pfontanillas@23andme.com</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39098/sda-long-read-sequence-and-assembly-of-segmental-duplications</guid>
	<pubDate>Tue, 05 Mar 2019 10:00:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39098/sda-long-read-sequence-and-assembly-of-segmental-duplications</link>
	<title><![CDATA[SDA: Long-read sequence and assembly of segmental duplications]]></title>
	<description><![CDATA[<p><span><span>Segmental Duplication Assembler (SDA; https://github.com/mvollger/SDA) constructs graphs in which paralogous sequence variants define the nodes and long-read sequences provide attraction and repulsion edges, enabling the partition and assembly of long reads corresponding to distinct paralogs.<br></span></span></p>
<p><span><span>https://github.com/mvollger/SDA</span></span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/s41592-018-0236-3" rel="nofollow">https://www.nature.com/articles/s41592-018-0236-3</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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