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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27459?offset=80</link>
	<atom:link href="https://bioinformaticsonline.com/related/27459?offset=80" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42664/common-bioinformatics-interview-questions</guid>
	<pubDate>Sat, 23 Jan 2021 06:07:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42664/common-bioinformatics-interview-questions</link>
	<title><![CDATA[Common Bioinformatics Interview Questions !]]></title>
	<description><![CDATA[<p>The possibility of an interview for a bioinformatics position in the life sciences may be very disquieting, but the same concerns emerge time and again in my experience. So, it is exceedingly worthwhile to plan for future bioinformatics interview questions. Doing this will really give you the advantage in obtaining the position.</p><p>The following 5 questions are those that I have heard many times during the job-search process. There is no reason for not planning responses in such situations.</p><p><strong>1. Tell Us About Yourself</strong><br />This is a very typical opener in interviews. It's a perfect question to ask, and getting something planned will really help you concentrate and ease in the conversation. However, you need to make sure that your response is applicable to the job you're interviewing.<br />It's probably better to keep your answer professional. Try to include these in the answer as well: where did your love of science and bioinformatics come from? How the heck did you end up in this field? Why programming and scripting ?</p><p><strong>2. What is your plan for your bioinformatics career? / How do you look at yourself in five years? / How are your personal objectives to accomplish these goals / What are the plan for your research fundings ?</strong></p><p>Your CV/resume has already impressed the selection panel if you have been invited for an interview. The questions from the bioinformatics interview team provide an incentive for you to market yourself and illustrate the work in question with the most appropriate knowledge.</p><p><strong>3. What do you understand about the job description/What would your suggested research path be if you were a successful candidate?</strong><br />Summarize the specifics of the advertised bioinformatics position in your own words. Follow on with some suggestions of how you want to extend your research and create your own projects within the community.</p><p><strong>4. Will you work as a group or do you want to work on your own?</strong><br />This requirement can vary from jobs to job, so when addressing, be alert. A company/research PI may need a bioinformatician that is able to work on a single project autonomously, or they may need a person who can help direct and organize a team. In your response, refer to the job description.</p><p><strong>5. What particular methods have you used to date with your experiments?</strong><br />You might have experience with all the laboratory techniques described in the job description, but stress the ones you highly experienced with. Highlight your professional abilities and stress that you are extremely capable of mastering new techniques with others ...</p><p>At the end of the day, remember that you're questioning the jury as well as they're interviewing you. You will ought to think of any questions you would like the interview panel to pose. This indicates that you have done your homework and serious about the position.</p><p>All the best for your future job interview.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44227/common-methods-to-discover-tandem-repeats</guid>
	<pubDate>Thu, 09 Mar 2023 02:40:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44227/common-methods-to-discover-tandem-repeats</link>
	<title><![CDATA[Common methods to discover tandem repeats]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Tandem repeats are DNA sequences that are repeated in a contiguous manner in the genome. These sequences are often used as genetic markers and are important in many areas of genetics and genomics research. Here are some methods for discovering tandem repeats in genomes:</p><ol>
<li>
<p>Tandem Repeat Finder: Tandem Repeat Finder is a software tool that identifies tandem repeats in DNA sequences. It is available for free download and can be used on both nucleotide and protein sequences. The tool uses a statistical algorithm to identify repeats based on their length, copy number, and overall composition.</p>
</li>
<li>
<p>RepeatMasker: RepeatMasker is another software tool that can identify tandem repeats in DNA sequences. It works by comparing the input sequence to a database of known repeats and then identifies any tandem repeats that match those in the database.</p>
</li>
<li>
<p>PCR-based methods: Polymerase chain reaction (PCR) can be used to amplify and detect tandem repeats in genomic DNA. PCR primers are designed to flank the tandem repeat region, and amplification of the target DNA fragment can be visualized on a gel. This method can be useful for detecting novel tandem repeats and for genotyping.</p>
</li>
<li>
<p>Southern blotting: Southern blotting is a classic method for detecting DNA fragments in a sample. It can be used to detect tandem repeats by digesting genomic DNA with a restriction enzyme, separating the fragments by gel electrophoresis, and then probing the blot with a tandem repeat-specific probe.</p>
</li>
</ol><p>Overall, a combination of these methods can be used to comprehensively identify tandem repeats in genomes.</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/pages/view/11735/search-shell-command-history</guid>
	<pubDate>Thu, 12 Jun 2014 17:43:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11735/search-shell-command-history</link>
	<title><![CDATA[Search Shell Command History]]></title>
	<description><![CDATA[<p>We use couple of hundreads of command in daily basis. Most of them are actually repeated several time. The question remain open how do I search old command history under bash shell and modify or reuse it? <br /><br />Now a days almost all modern shell allows you to search command history if enabled by user. Use history command to display the history list with line numbers. Lines listed with with a * have been modified by user.</p><p><br /><strong>Shell history search command</strong><br /><br />Type history at a shell prompt:<br />$ history</p><p>It will display the list of all used commandline history with an serial number.<br /><br />To search particular command, enter:<br />$ history | grep command-name<br />$ history | egrep -i 'scp|ssh|ftp'<br />Emacs Line-Edit Mode Command History Searching<br /><br />To get previous command containing string, hit [CTRL]+[r] followed by search string:<br /><br />(reverse-i-search): <br /><br />To get previous command, hit [CTRL]+[p]. You can also use up arrow key.<br /><br />CTRL-p<br /><br />To get next command, hit [CTRL]+[n]. You can also use down arrow key.<br /><br />CTRL-n<br /><br /></p><p><strong>fc command</strong></p><p>Apart from hostory command there are fc command to extract the command from history. The fc stands for either "find command" or "fix command.</p><p>For example list last 10 command, enter:<br />$ fc -l 10<br />To list commands 130 through 150, enter:<br />$ fc -l 130 150<br />To list all commands since the last command beginning with ssh, enter:<br />$ fc -l ssh<br />You can edit commands 1 through 5 using vi text editor, enter:<br />$ fc -e vi 1 5</p><p><strong>Delete command history</strong><br /><br />The -c option causes the history list to be cleared by deleting all of the entries:<br />$ history -c</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36395/ligand-docking-tools-and-software</guid>
	<pubDate>Wed, 25 Apr 2018 05:05:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36395/ligand-docking-tools-and-software</link>
	<title><![CDATA[Ligand Docking Tools and Software !]]></title>
	<description><![CDATA[<p>Ligand docking referred to cases where small molecule (&ldquo;ligand&rdquo;) is being docked into much larger macromolecule ("target"). The following is partial list of docking software, focusing on free (at least for academic institutes) and/or popular docking tools.&nbsp;</p><p><a href="http://autodock.scripps.edu/" target="_blank">AutoDock</a></p><p>Stochastic (GA)</p><p>Flexible ligand and partially flexible target</p><p><a href="http://www.arguslab.com/" target="_blank">ArgusLab</a></p><p>Systematic</p><p>Flexible ligandX-Score based</p><p><a href="http://dock.compbio.ucsf.edu/" target="_blank">DOCK</a></p><p>Systematic (IC)</p><p>Flexible ligandDOCK 3.5 (force field)</p><p><a href="http://www.simbiosys.ca/ehits/index.html" target="_blank">eHITS</a></p><p>Systematic (RBD of fragments followed by reconstruction)Flexible ligand and partially flexible targetHiTS_Score (empirical)</p><p><a href="http://www.biosolveit.de/" target="_blank">FlexX</a></p><p>Systematic (IC)Flexible ligandFlexX SF (empirical)Commercial</p><p><a href="http://flipdock.scripps.edu/" target="_blank">FLIPDock</a></p><p>Stochastic (GA)Flexible ligand and flexible targetAUTODOCK (empirical)</p><p><a href="http://www.eyesopen.com/products/applications/fred.html" target="_blank">FRED</a></p><p>Systematic (RBD)Flexible ligandChemScore, PLP, ScreenScore, ChemGauss (empirical/consensus)</p><p><a href="http://www.ccdc.cam.ac.uk/products/life_sciences/gold/" target="_blank">GOLD</a></p><p>Stochastic (GA)</p><p>Flexible ligand and partially flexible targetGoldScore, ChemScore (empirical), ASP (knowledge based)</p><p><a href="http://www.molsoft.com/docking.html" target="_blank">ICM</a></p><p>Stochastic (MC)</p><p>Flexible ligand and partially flexible targetICM SF (empirical)</p><p><a href="http://www.scfbio-iitd.res.in/dock/pardock.jsp" target="_blank">ParDOCK</a></p><p>Stochastic (MC)</p><p>RigidBAPPL (empirical)</p><p><em><a href="http://www.scfbio-iitd.res.in/dock/pardock.jsp" target="_blank"></a></em><a href="http://www.tcd.uni-konstanz.de/research/plants.php" target="_blank">PLANTS</a></p><p>Stochastic (ACO)Flexible ligand and partially flexible target</p><p>CHEMPLP, PLP (empirical)</p><p><a href="http://www.biopharmics.com/" target="_blank">Surflex</a></p><p>Systematic (IC/MA)Flexible ligandHammerhead based (empirical)</p><p>Point to note:</p><p>Several studies have shown that the performance of most docking tools is highly dependent on the particular characteristics of both the binding site and the ligand to be investigated, and the determination which method would be more suitable in a specific context is difficult. We encouraged you to check several docking methods to determine which one(s) work best for your system.</p><p>&nbsp;</p><p><a href="http://autodock.scripps.edu/" target="_blank"></a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38743/molinspiration-broad-range-of-cheminformatics-software-tools-supporting-molecule-manipulation</guid>
	<pubDate>Sun, 20 Jan 2019 05:32:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38743/molinspiration-broad-range-of-cheminformatics-software-tools-supporting-molecule-manipulation</link>
	<title><![CDATA[molinspiration: broad range of cheminformatics software tools supporting molecule manipulation]]></title>
	<description><![CDATA[<p><span>Molinspiration offers&nbsp;</span><a href="https://www.molinspiration.com/products.html">broad range of cheminformatics software tools</a><span>&nbsp;supporting molecule manipulation and processing, including SMILES and SDfile conversion, normalization of molecules, generation of tautomers, molecule fragmentation, calculation of various molecular properties needed in QSAR, molecular modelling and drug design, high quality molecule depiction, molecular database tools supporting substructure and similarity searches. Our products support also fragment-based virtual screening, bioactivity prediction and data visualization. Molinspiration tools are written in Java, therefore can be used practically on any computer platform.</span></p><p>Address of the bookmark: <a href="https://www.molinspiration.com/" rel="nofollow">https://www.molinspiration.com/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</guid>
	<pubDate>Sun, 07 Mar 2021 00:32:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42936/ancient-whole-genome-duplication-wgd-detection-tools</link>
	<title><![CDATA[Ancient whole genome duplication (WGD) detection tools !]]></title>
	<description><![CDATA[<p>There are two methods for ancient WGD detection, one is collinearity analysis, and the other is based on the Ks distribution map. Among them, Ks is defined as the average number of synonymous substitutions at each synonymous site, and there is also a Ka corresponding to it, which refers to the average number of non-synonymous substitutions at each non-synonymous site.</p><p>At present, some people have posted articles about the analysis process of WGD. I searched for the keyword "wgd pipeline" and found the following:</p><p><strong>GenoDup: https:// github.com/MaoYafei/GenoDup-Pipeline</strong><br /><strong>https://peerj.com/articles/6303/</strong><br /><strong>WGDdetector: https:// github.com/yongzhiyang2 012/WGDdetector</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3</strong><br /><strong>wgd: https:// github.com/arzwa/wgd</strong><br /><strong>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2#Sec1</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>GeNoGAP https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2</strong><br /><strong>https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x</strong><br /><strong>https://github.com/dfguan/purge_dups</strong><br /><strong>https://www.biorxiv.org/content/10.1101/2020.01.24.917997v1</strong></p><p>This article introduces the usage of wgd.</p><p>Wgd cannot be installed directly with bioconda at present, so it is a little troublesome to install, because it depends on a lot of software. wgd depends on the following software</p><p><strong>BLAST</strong><br /><strong>MCL</strong><br /><strong>MUSCLE/MAFFT/PRANK</strong><br /><strong>PAML</strong><br /><strong>PhyML/FastTree</strong><br /><strong>i-ADHoRe</strong></p><p>But the good news is that most of the software it depends on can be installed with bioconda</p><blockquote><p>conda create -n wgd python=3.5 blast mcl muscle mafft prank paml fasttree cmake libpng mpi=1.0=mpich<br />conda activate wgd</p></blockquote><p>Here mpi=1.0=mpich is selected, because i-adhore depends on mpich. If openmpi is installed, an error will appear while loading shared libraries: libmpi_cxx.so.40: cannot open shared object file: No such file or directory</p><p>After that, the installation is much simpler</p><blockquote><p>git clone https://github.com/arzwa/wgd.git<br />cd wgd<br />pip install .<br />pip install git+https://github.com/arzwa/wgd.git<br />For i-ADHoRe, you need to register at http:// bioinformatics.psb.ugent.be /webtools/i-adhore/licensing/Agree to the license to download i-ADHoRe-3.0</p></blockquote><p>Since my miniconda3 installed ~/opt/, the installation path is so~/opt/miniconda3/envs/wgd/</p><blockquote><p>tar -zxvf i-adhore-3.0.01.tar.gz<br />cd i-adhore-3.0.01<br />mkdir -p build &amp;&amp; cd build<br />cmake .. -DCMAKE_INSTALL_PREFIX=~/opt/miniconda3/envs/wgd/<br />make -j 4 <br />make insatall</p></blockquote><p>Take the sugarcane genome Saccharum spontaneum L as an example. The genome is 8-ploid with 32 chromosomes (2n = 4x8 = 32)</p><p><strong>Download the tutorial for CDS and GFF annotation files</strong></p><blockquote><p><strong>mkdir -p wgd_tutorial &amp;&amp; cd wgd_tutorial</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.cds.fasta.gz</strong><br /><strong>wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.gff3.gz</strong><br /><strong>gunzip *.gz</strong></p></blockquote><p>First conda activate wgdstart our analysis environment, and then start the analysis</p><p>Step 1 : Use to wgd mclidentify homologous genes in the genome</p><blockquote><p>wgd mcl -n 20 --cds --mcl -s Sspon.v20190103.cds.fasta -o Sspon_cds.out</p></blockquote><p>Step 2 : Use to wgd ksdbuild Ks distribution</p><blockquote><p>wgd ksd --n_threads 80 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl Sspon.v20190103.cds.fasta</p></blockquote><p>Step 3 : If the quality of the genome is good, then wgd syncollinearity analysis can be used . It can help us find the collinearity block in the genome and the corresponding anchor point</p><blockquote><p>wgd syn --feature gene --gene_attribute ID \<br /> -ks wgd_ksd/Sspon.v20190103.cds.fasta.ks.tsv \<br /> Sspon.v20190103.gff3 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl</p></blockquote><p>&nbsp;For more reading - There are 9 sub-modules in WGD</p><ul>
<li><span>kde: KDE fitting to the Ks distribution</span></li>
<li><span>ksd: Ks distribution construction</span></li>
<li><span>mcl: BLASP comparison of All-vs-ALl + MCL classification analysis.</span></li>
<li><span><span>mix: Hybrid modeling of Ks distribution.</span></span></li>
<li><span>pre: preprocess the CDS file</span></li>
<li><span>syn: Call I-ADHoRe 3.0 to use GFF files for collinearity analysis</span></li>
<li><span>viz: draw histogram and density plot</span></li>
<li><span>wf1: Ks standard analysis procedure of the whole genome paranome (paranome), call mcl, ksd and syn</span></li>
<li><span>wf2: Ks standard analysis procedure of one-vs-one homologous gene (ortholog), call wcl and kSD</span></li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19090/deeptools</guid>
	<pubDate>Sat, 08 Nov 2014 15:02:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19090/deeptools</link>
	<title><![CDATA[deepTools]]></title>
	<description><![CDATA[<p>deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. To do so, deepTools contains useful modules to process the mapped reads data to create coverage files in standard bedGraph and bigWig file formats. By doing so, deepTools allows the creation of normalized coverage files or the comparison between two files (for example, treatment and control). Finally, using such normalized and standardized files, multiple visualizations can be created to identify enrichments with functional annotations of the genome.<br /><br />Publicaton: http://nar.oxfordjournals.org/content/early/2014/05/05/nar.gku365.full<br /><br />Source Code and Wiki: https://github.com/fidelram/deepTools/wiki<br /><br />Galaxy Tool Shed repository: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools<br /><br />and example Galaxy workflows: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools_workflows</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24297/bioinformatics-walkin-at-nii</guid>
  <pubDate>Fri, 04 Sep 2015 21:48:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics WalkIn at NII]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT OF WALK-IN-INTERVIEW</p>

<p>NAME OF THE POST : Bioinformatician (Part time 3 days in a week) (One Position only)</p>

<p>DURATION : One Year</p>

<p>NAME OF THE PROJECT : Next generation sequencing facility</p>

<p>EDUCATIONAL QUALIFICATIONS : At least a Masters degree in Bioinformatics and Bachelors degree in any stream of life sciences</p>

<p>REQUIREMENTS :</p>

<p>Around 5 years of experience and proven track record in next generation sequence data analysis (supported by publications in peer-reviewed journals), ability to analyze transcriptomics, Chip-seq, and small RNA –seq data.</p>

<p>: Should have the ability to analyze raw primary data generated by Illumina next generation sequencing platforms and create / troubleshoot custom analysis Pipelines.</p>

<p>Should have ability to handle all downstream secondary and tertiary data analysis using commercially available as well as open source softwares (transcriptomics, ChIP-seq, small RNA-seq)</p>

<p>Apart from these, the applicant should have knowledge of the following: Programming: Perl and Python. Operating system:</p>

<p>Linux and Windows. NGS Analysis tools: Maq, BWA, Bowtie, SAM tools, BEDTools, MACS, Galaxy, FastQC, Bismark, MEDIPS, Tophat, Cufflinks, AvadisNGS, CLC Genomics Workbench, Galaxy, BaseSpace, Trinity Statistics: Microsoft Excel and R. Database: MySQL Genome Browser: UCSC, Ensemble, IGV, IGB Motif Analysis Tools: MEME Suite, Transfac and RSAT Functional Annotation Tools: DAVID, GeneCodis, Gene Cards Networking Tools: Cytoscape</p>

<p>EMOLUMENTS : The incumbent will be paid a fee of Rs. 2000/- per sitting/ per day.</p>

<p>SCIENTIST NAME : Dr. Arnab Mukhopadhyay,</p>

<p>Staff Scientific V Next generation sequencing facility</p>

<p>SCIENTIST’S E-MAIL ID : arnab@nii.ac.in</p>

<p>WALK IN INTERVIEW ON : 18th September, 2015</p>

<p>REGISTRATION OF CANDIDATES: 10.30 AM to 11.00 AM</p>

<p>PLEASE NOTE- 1. CANDIDATE MAY FILL UP APPLICATION IN THE PRECRIBED FORMAT ALONG WITH NECESSARY DOCUMENTS FOR VERIFICATION. 2. APPLICATIONS CONTAINING INCOMPLETE INFORMATION SHALL NOT BE ENTERTAINED. 3. DATE OF PASSING THE EXAMINATIONS MUST BE INDICATED CLEARLY. 4. ONLY REGISTERED CANDIDATES WILL BE INTERVIEWED. 5. NO TA/DA WILL BE PAID FOR ATTENDING THE INTERVIEW PRESCRIBED FORM 1. NAME 2. FATHER’S NAME 3. MOTHER’S NAME 4. DATE OF BIRTH 5. SEX (MALE/FEMALE) 6. CATEGORY (SC/ ST/ OBC/ PH) 7. ADDRESS a. (CORRSPONDENCE) b. (PERMANENT) 8. E MAIL, TELEPHONE NO. &amp; MOBILE No (if any) 9. ACADEMIC &amp; PROFESSIONAL QUALIFICATIONS NAME OF EXAMINATION PASSED WITH SUBJECTS YEAR OF PASSING BOARD/ UNIVERSITY PERCENTAGE/ DIVISION REMARKS 10. PAST EXPERIENCE &amp; PRESENT EMPLOYMENT, IF ANY 11. CANDIDATES SHOULD STATE CLEARLY WHETHER THEY HAVE BEEN AWARDED PH.D DEGREE OR THESIS HAS BEEN SUBMITTED. 12. HAVE YOU APPLIED FOR A POSITION EARLIER IN THE INSTITUTE? IF SO:- (1) THE DETAILS OF THE PROJECT AND PROJECT INVESTIGATOR (2) IF CALLED FOR INVERVIEW, RESULTS THEREOF</p>

<p>More at http://www1.nii.res.in/sites/default/files/walkininterview-18sept2015.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25410/srfjrf-bioinformatics-at-ciari</guid>
  <pubDate>Fri, 04 Dec 2015 00:10:09 -0600</pubDate>
  <link></link>
  <title><![CDATA[SRF/JRF Bioinformatics at CIARI]]></title>
  <description><![CDATA[
<p>Realizing the importance of Island Agriculture to meet the requirements of local population and tourists, Indian Council of Agricultural research (ICAR) established Central Island Agricultural Research Institute, Port Blair on June 23rd, 1978 by merging different regional research stations of ICAR institutes located in Islands. The ultimate aim of CIARI is the developments of island agricultural production technologies which utilizes the strengths of the island and convert the constraints in opportunities, without causing any ill effect to the fragile ecosystem of the island.The institute has made tremendous progress in the Agriculture development of the islands during the last three decades. Keeping in view the natural resources of the islands diversity, fragile ecosystem, research program would be designed to maximize the productivity without disturbing to the islands ecosystem to provide better and decent livelihood and as a source of revenue and resource generation. Research and development in Agriculture sector should cover all disciplines in order to have a balanced progress in all disciplines for the overall benefits of the farmers of these islands.</p>

<p>Position I</p>

<p>Job Title : Junior Research Fellow</p>

<p>No. of Posts : One</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : M.Sc in Basic Science with NET or B.Sc in professional course with NET or M.Sc in professional course</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 25000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>Position II</p>

<p>Job Title : Traineeship</p>

<p>No. of Posts : One</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : B.Sc Bioinformatics /Biotechnology / Life Science / Computer Science</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 8000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>Position III</p>

<p>Job Title : Studentship</p>

<p>No. of Posts : Two</p>

<p>Project : Establishment of sub distributed information centre</p>

<p>Qualification : B.Sc Bioinformatics /Biotechnology / Life Science / Computer Science</p>

<p>Desired Experience : Experience in Bioinformatics and molecular biology</p>

<p>Payscale : Rs. 8000 per month</p>

<p>Age Limit : Upto 35 for men and 40 for women with 5 years relaxation to SC/ST and 3 years relaxation for OBC.</p>

<p>How to Apply : Candidates who meet the requirements can attend the walk in interview at CIARI,Port Blair on 09.12.2015 10.30AM.</p>

<p>http://icar-ciari.res.in/employment/9-12-15.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/25674/post-doc-position-at-labgem-evry-france</guid>
  <pubDate>Fri, 11 Dec 2015 06:24:00 -0600</pubDate>
  <link></link>
  <title><![CDATA[Post-doc position at LABGeM - Evry, France]]></title>
  <description><![CDATA[
<p>The LABGeM team (CEA/Genoscope, CNRS UMR 8030, France, Dir. Claudine Médigue) is developing integrated approaches which combines bioinformatics methods based (i) on genomic and metabolic contexts, (ii) on an orignal metabolic network representation and (iii) on a structural classification of active sites for the discovery of new metabolic enzymatic activities.</p>

<p>We are hiring a post-doctoral fellow for the development of innovative bioinformatics methods to explore metabolic networks and enzyme families. These methods will be based on protein family analysis and graph approaches combining genomic and metabolic contexts.</p>

<p>For more details, please see this link : http://goo.gl/tHQOqk</p>

<p>Qualifications:<br />PhD degree in bioinformatics or computational biology<br />- Previous experience in network or protein family analysis<br />- Programming skills (C/C++, Python, Java) and in common biostatistical analyses<br />- Team player, innovative and creative thinking, good oral and written communication skills</p>

<p>24 months, Post Doctoral position<br />Start: from March 2016<br />Place: CEA, Genoscope UMR8030, LABGeM (Laboratory of Bioinformatics Analyses for Genomics and Metabolism), Evry, France<br />Contact: David Vallenet, vallenet@genoscope.cns.fr<br />Publications: https://scholar.google.com/citations?user=rJNPLSAAAAAJ<br />Remuneration per month: from 2,850 €</p>

<p>Interested candidates should send their CV, statement of research interests, and contact information of at least 2 references to David Vallenet (vallenet@genoscope.cns.fr).</p>
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