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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27438?offset=880</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12566/jrf-at-national-research-centre-on-plant-biotechnology</guid>
  <pubDate>Fri, 04 Jul 2014 13:36:02 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF at NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY]]></title>
  <description><![CDATA[
<p>NATIONAL RESEARCH CENTRE ON PLANT BIOTECHNOLOGY</p>

<p>New Delhi-110012</p>

<p>Walk in interview</p>

<p>Eligible candidates may appear for Walk-in interview for the temporary positions of JRF/SRF/ RA, in ICAR, DBT funded research projects. Positions are purely temporary in nature and are co-terminus with the projects. The initial appointment will be for maximum one year, which can be extended on the basis of assessment of the candidate performance and need in the project work (PI-Dr. N. K. Singh, National Professor).</p>

<p>Name of the</p>

<p>PI (Project)<br />	</p>

<p>Name of</p>

<p>Position<br />	</p>

<p>Number of</p>

<p>positions<br />	</p>

<p>Emoluments</p>

<p>Fixed per</p>

<p>month (Rs.)<br />	</p>

<p>Essential</p>

<p>Qualifications</p>

<p>DBT-“Physical Mapping and Sample sequencing of Wheat Chromosome 2A- International Wheat Genome Sequencing Consortium (India)”.</p>

<p>(Up to Nov,2014)</p>

<p>DBT- Identification and functional analysis of genes related to yield and biotic stresses (Up to Oct,2014)</p>

<p>NPTC-Central Facility<br />	</p>

<p>RA (Master)</p>

<p>JRF/SRF</p>

<p>Research Associate: One</p>

<p>Essential: MCA or M. Tech. (Bioinformatics and computer Science with 2 years experience in Database Management with</p>

<p>MySQL, Linux)</p>

<p>Desirable: Proficiency in handling of large biological databases</p>

<p>Age limit: Max. Age 35 years (Age of relaxation of 5 years for SC/ST&amp; woman. and 3 years for OBC). The interview will be held on 08 July, 2014 at 11 am at room no. 39, NRCPB, LBS Building, Pusa Campus, New Delhi-110012. The candidates must bring original certificates and four copies of biodata, and recent passport size photograph. No TA/DA would be given for the appearance in interview. Only the candidates having essential qualifications would be entertained for the interviews.</p>

<p>Advertisement:</p>

<p>www.nrcpb.org/sites/default/files/news%20paper%20advirtisment..docx</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12988/guest-lecturer-molecular-biology-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 13:34:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Guest Lecturer - Molecular Biology &amp; Bioinformatics]]></title>
  <description><![CDATA[
<p>Adv. No. F.TU/ACA/GT-APP/01/14 Date: 07.07.2014</p>

<p>Faculty of Science</p>

<p>Essential Qualifications:</p>

<p>(i) Good academic record having at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master’s Degree level in a relevant subject, from an Indian University, or an equivalent degree from an accredited foreign University.</p>

<p>(II) Besides fulfilling the above qualifications, the candidates must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET.</p>

<p>(III) Notwithstanding anything contained in sub-clauses (i) and (ii) of clause 4.4.1 of UGC regulations 2010, candidates, who are, or have been awarded a Ph.D. Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations, 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/ SLET/ SET for engagement of guest Teacher.</p>

<p>(IV) NET/ SLET/ SET shall also not be required for such Master’s Degree Programmes in discipline for which NET/ SLET/ SET is not conducted.</p>

<p>Application form along with detailed instructions can be downloaded from Tripura University website: www.tripurauniv.in. The duly filled in application forms complete in all respects may be sent so as to reach the Office of the Deputy Registrar Academic Branch, Tripura University, Suryamaninagar - 799022, Tripura on or before 31st July, 2014. The Candidates who responded against advertisement No. TU.REG/N-Advt./02/10 dated 20.02.2014 need not apply again.</p>

<p>For more info visit: http://www.tripurauniv.in/images/universitymedia/EmploymentNotification/Guest%20Teacher%20Advt.%20website_09072014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37746/funannotate-eukaryotic-genome-annotation-pipeline</guid>
	<pubDate>Wed, 19 Sep 2018 07:47:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37746/funannotate-eukaryotic-genome-annotation-pipeline</link>
	<title><![CDATA[funannotate: Eukaryotic Genome Annotation Pipeline]]></title>
	<description><![CDATA[<p><span>Funannotate is a genome prediction, annotation, and comparison software package. It was originally written to annotate fungal genomes (small eukaryotes ~ 30 Mb genomes), but has evolved over time to accomodate larger genomes. The impetus for this software package was to be able to accurately and easily annotate a genome for submission to NCBI GenBank. Existing tools (such as Maker) require significant manually editing to comply with GenBank submission rules, thus funannotate is aimed at simplifying the genome submission process.</span></p><p>Address of the bookmark: <a href="https://github.com/nextgenusfs/funannotate" rel="nofollow">https://github.com/nextgenusfs/funannotate</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36950/salsa-a-tool-to-scaffold-long-read-assemblies-with-hi-c</guid>
	<pubDate>Fri, 15 Jun 2018 04:01:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36950/salsa-a-tool-to-scaffold-long-read-assemblies-with-hi-c</link>
	<title><![CDATA[SALSA: A tool to scaffold long read assemblies with Hi-C]]></title>
	<description><![CDATA[This code is used to scaffold your assemblies using Hi-C data. This version implements some improvements in the original SALSA algorithm. If you want to use the old version, it can be found in the old_salsa branch.

To use the latest version, first run the following commands:

  cd SALSA
  make
To run the code, you will need Python 2.7, BOOST libraries and Networkx(version lower than 1.2).

If you consider using this tool, please cite our publication which describes the methods used for scaffolding.

Ghurye, J., Pop, M., Koren, S., Bickhart, D., &amp; Chin, C. S. (2017). Scaffolding of long read assemblies using long range contact information. BMC genomics, 18(1), 527. Link

Ghurye, J., Rhie, A., Walenz, B.P., Schmitt, A., Selvaraj, S., Pop, M., Phillippy, A.M. and Koren, S., 2018. Integrating Hi-C links with assembly graphs for chromosome-scale assembly. bioRxiv, p.261149 Link

For any queries, please either ask on github issue page or send an email to Jay Ghurye (jayg@cs.umd.edu).<p>Address of the bookmark: <a href="https://github.com/machinegun/SALSA" rel="nofollow">https://github.com/machinegun/SALSA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12936/assistant-professor-medical-bioinformatics</guid>
  <pubDate>Wed, 23 Jul 2014 05:00:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor - Medical Bioinformatics]]></title>
  <description><![CDATA[
<p>Advt. No : ME-I/A-IV/03/14</p>

<p>No.of Posts:01 (SC)</p>

<p>Pay Scale:</p>

<p>Pay Band of Rs.15600-39100 + Rs.6000/- GP +NPA @ 25% of Basic Pay +Learning Resource Allowance @ Rs.20,000/-P.A.+ Conveyance Allowance @ Rs. 1650/-P.M.+ Academic Allowance @ Rs.2500/- P.M. and other admissible allowances.</p>

<p>Qualifications:</p>

<p>Area of Specialization:-</p>

<p>Bioinformatics/Computational/Biology/Genomics/ Proteomics/ Structural Biology</p>

<p>1. Postgraduate qualification, e.g. Master’s Degree in Biotechnology/Bioinformatics/ Biophysics.</p>

<p>2. A Doctorate Degree of recognized University/Institute in a basic or allied Medical Science subject e.g. Medical Biotechnology/Biophysics. Bioinformatics/X-ray Crystallography/</p>

<p>Immunology/Structural Biology etc</p>

<p>Experience:</p>

<p>1.Minimum three years teaching and/or research experience in a recognized medical/research Institution in an allied medical subject after obtaining doctorate degree and preferably in Medical</p>

<p>Molecular Biology/ Biophysics/Structural Biology/Genomics and Clinical Proteomics/Computational Biology.</p>

<p>2. Minimum two publication with atleast one in international journal and atleast one as first author</p>

<p>Desirable:-</p>

<p>Consistently excellent scholastic/academic record, demonstrated ability to write grant proposal/(s) successfully, Post Doctoral training in a frontier area of medical Bioinformatics Research and of direct relevance to clinical diagnosis or patient care (preferably from a recognized top-ranking medical institution abroad)</p>

<p>Send your applications to O/O, Deputy Registrar, Recruitment &amp; Establishment Cell, University of Health Sciences, Rohtak by 08.7.2014</p>

<p>For more details,please visit website:http://pgimsrohtak.nic.in/2014%20AP%20Advt.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</guid>
	<pubDate>Thu, 24 Jul 2014 02:51:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/13025/the-5-reasons-to-mistakes-at-bioinformatics-work</link>
	<title><![CDATA[The 5 reasons to mistakes at bioinformatics work !!!]]></title>
	<description><![CDATA[<p>When you're just starting out with biological programming, it's easy to run into complex problems that make you wonder how anyone has ever managed to write a program. There are some problems that trip up nearly every bioinformatician--everything from getting started understanding the biological problems to dealing with program design. Some random mistakes are so prominent that even experienced biological programmers do it. The 8 years in bioinformatics and my few random observations, most of them are snarky. These reasons will always take longer than expected and compel you to postpone your project deadline.</p><p><strong>1.Stupid for biologist:</strong> Biology is so complex that it will make bioinformatician feel stupid. There are no any universal fixed rules; it can surprise you any time. So be nice to biologists who ask questions and resolve your biological puzzles. Sometime you will have no idea what the hell you were doing either.<br /><br /><strong>2.Puzzling why:</strong> Do not hesitate to ask question. Especially. at the beginning of project you will have to ask a lot of questions. Instead of puzzling it out at end check out and clear your doubt even for a single error. It may can leads to wrong conclusion.<br /><br /><strong>3.Running marathon:</strong> The most of the biological software&rsquo;s documentation is always incomplete. In other word they are no more than 95 percent complete. Sometime a single problem can halt your entire project for months. Compilation and running the pipelines in tedious because almost all are interdependent and need proper configuration. I face the same kind of problem with Evolver :( &hellip; <br /><br /><strong>4.Folders missing:</strong> The pipelines generate lots of data, and we keep them in several folders for future use. But sometime we delete them by mistake and move to recovery&hellip;<br /><br /><strong>5.Digging deeper:</strong> Digging deeper is fruitful, but some time it can be catastrophic. You may get frustrated or direction less. So keep a biologist with you for rescue &hellip;. Sometime an expert computer programmer to handle your server. Remember, the server will always go down when you need it the most.<br /><br />The most common frustrating&nbsp; common line: Why do we do this again?</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38441/genome-sequence-based-sub-species-delineation</guid>
	<pubDate>Wed, 12 Dec 2018 08:31:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38441/genome-sequence-based-sub-species-delineation</link>
	<title><![CDATA[Genome sequence-based (sub-)species delineation.]]></title>
	<description><![CDATA[<p>The GGDC web service reports digital DDH for a universal and accurate delineation of prokaryotic (sub-)species without inheriting the pitfalls of classic DDH, and also calculates differences in genomic G+C content.</p>
<p>http://ggdc.dsmz.de/ggdc_background.php#</p>
<p><small>Genome-to-Genome Distance Calculator 2.1</small></p>
<p>http://ggdc.dsmz.de/ggdc.php</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://ggdc.dsmz.de/" rel="nofollow">http://ggdc.dsmz.de/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13338/protein-function-annotation-and-machine-learning-upmc-paris-france</guid>
  <pubDate>Sat, 02 Aug 2014 01:22:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Protein function annotation and machine learning - UPMC - Paris, France]]></title>
  <description><![CDATA[
<p>Protein function annotation and machine learning - UPMC - Paris, France</p>

<p>Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.</p>

<p>We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.</p>

<p>Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>Start date: September 1st, 2014<br />Contact Person: Alessandra Carbone<br />Contact: alessandra.carbone@lip6.fr</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/39217/caulobacter-ethensis-20-computer-generated-genome-of-a-living-organism</guid>
	<pubDate>Wed, 03 Apr 2019 08:45:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/39217/caulobacter-ethensis-20-computer-generated-genome-of-a-living-organism</link>
	<title><![CDATA[Caulobacter ethensis - 2.0 : Computer-generated Genome of a Living Organism]]></title>
	<description><![CDATA[<div><span>All the genome sequences of organisms known throughout the world are stored in a database belonging to the National Center for Biotechnology Information in the United States. As of today, the database has an additional entry:&nbsp;<em><strong><span>Caulobacter ethensis</span></strong></em><span><strong><span>-2.0</span></strong>.&nbsp;</span></span></div><div><span><span>&nbsp;</span></span></div><div><span><span>It is the&nbsp;<strong>world's first fully computer-generated genome of a living organism</strong>, developed by scientists at ETH Zurich.&nbsp;</span></span></div><div><span><span>&nbsp;</span></span></div><div><span><span>However, it must be emphasised that although the genome for&nbsp;</span><em>C. ethensis</em>-2.0 was physically produced in the form of a very large DNA molecule, a corresponding organism does not yet exist.</span></div><div><span>&nbsp;</span></div><div><span><strong>Source</strong>:&nbsp;<a href="https://www.sciencedaily.com/releases/2019/04/190401171343.htm?utm_source=feedburner&amp;utm_medium=email&amp;utm_campaign=Feed%3A+sciencedaily%2Fmost_popular+%28Most+Popular+News+--+ScienceDaily%29">https://www.sciencedaily.com/releases/2019/04/190401171343.htm</a></span></div>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</guid>
	<pubDate>Fri, 17 Jan 2020 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</link>
	<title><![CDATA[MGSE: Mapping-based Genome Size Estimation]]></title>
	<description><![CDATA[<p>MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script construct_cov_file.py (https://doi.org/10.1186/s12864-018-5360-z) allows the generation of a COV file based on the (sorted) BAM file (also possible via MGSE directly). Next, this COV file can be used by MGSE to calculate the coverage in provided reference regions and to calculate the total number of mapped bases. Both values are subjected to the genome size estimation. Providing accurate reference regions is crucial for this genome size estimation.</p><p>Address of the bookmark: <a href="https://github.com/bpucker/MGSE" rel="nofollow">https://github.com/bpucker/MGSE</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

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