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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26332?offset=400</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/10739/science-for-life-laboratory-scilifelab-sweden</guid>
  <pubDate>Sat, 10 May 2014 06:22:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Science for Life Laboratory (SciLifeLab)-Sweden]]></title>
  <description><![CDATA[
<p>Science for Life Laboratory (SciLifeLab) is a national center for molecular biosciences with focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource and a collaboration between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University.</p>

<p>Webpage : https://www.scilifelab.se/about-us/<br />Opportunity: https://www.scilifelab.se/about-us/career/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11582/monitor-running-jobs-on-linux-server</guid>
	<pubDate>Fri, 06 Jun 2014 16:18:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11582/monitor-running-jobs-on-linux-server</link>
	<title><![CDATA[Monitor running jobs on Linux server]]></title>
	<description><![CDATA[<p>You as a bioinformatican run lots of program on your servers. Sometime the shared server is also used by your colleague. If server is busy you sometime need to check the running programs and want to monitor the running programs as well. The "top" command will come in handy when you need to find out if things are still running, how long they&rsquo;ve been running, or how much memory is being used.<br /><br />&lsquo;top&rsquo; is very simple to run: type<br /><br />%% top<br /><br />You&rsquo;ll get a screen that looks like this, and is updated regularly:<br /><br /><img src="http://bioinformaticsonline.com/mod/photo/top.png" width="659" height="582" alt="image" style="border: 0px;"><br />Simple, right? Heh.<br /><br />First! Note that you can use &lsquo;q&rsquo; or &lsquo;CTRL-C&rsquo; to exit from &lsquo;top&rsquo;.<br /><br />Now let&rsquo;s read and understand at each line independently.<br /><br />The first line:<br /><br />top - 23:00:48 up 39 days,&nbsp; 2 user,&nbsp; load average: 0.00, 0.00, 0.00<br /><br />The first line tells you the current time, how long the machine has been up, how many users are logged in, and the short/medium/long-term compute load on the machine. If you run something for a long time, you&rsquo;ll see these numbers go up. Right now, the machine is basically just sitting there, so these are all close to 0.<br /><br />The second line:</p><p>Tasks:&nbsp; 239 total,&nbsp;&nbsp; 1 running,&nbsp; 238 sleeping,&nbsp;&nbsp; 0 stopped,&nbsp;&nbsp; 0 zombie<br /><br />This line tells you how many processes are running. If you are using laptops machines it&rsquo;s not so interesting because you really are the only one using this machine.<br /><br />Cpu(s):&nbsp; 0.0%us,&nbsp; 0.0%sy,&nbsp; 0.0%ni,100.0%id,&nbsp; 0.0%wa,&nbsp; 0.0%hi,&nbsp; 0.0%si,&nbsp; 0.0%st<br /><br />This line contains the CPU load. The first two numbers are how busy the system is doing computation (&ldquo;us&rdquo; stands for &ldquo;user&rdquo;) and how busy the system is doing system-y things like accessing disks or network (&ldquo;sy&rdquo; stands for &ldquo;system&rdquo;). We&rsquo;ll talk more about this later.<br /><br />Mem:&nbsp;&nbsp; 49457320k total,&nbsp;&nbsp;&nbsp; 3492174k used,&nbsp; 14535596k free,&nbsp;&nbsp;&nbsp; 1435148k buffers<br /><br />This should be easy to understand &ndash; how much memory you&rsquo;re using! <br /><br />Swap:&nbsp;&nbsp; 539356k total,&nbsp;&nbsp; 28332k used,&nbsp;&nbsp; 836562k free,&nbsp;&nbsp;&nbsp; 29862014k cached<br /><br />Swap is just on-disk memory that can be used to &ldquo;swap&rdquo; out programs from main memory. Again, we&rsquo;ll talk about this later.:<br /><br />PID USER&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PR&nbsp; NI&nbsp; VIRT&nbsp; RES&nbsp; SHR S %CPU %MEM&nbsp;&nbsp;&nbsp; TIME+&nbsp; COMMAND<br />&nbsp; 1 root&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 39 &nbsp; 19&nbsp; 0&nbsp; 0&nbsp; 0 S&nbsp; 0.0&nbsp; 0.0&nbsp;&nbsp; 246:57.22 kipmi0<br />&nbsp; 2 root&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; RT&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp; 0 S&nbsp; 0.0&nbsp; 0.0&nbsp;&nbsp; 0:00.00 migration/0<br /><br />And... finally! What&rsquo;s actually running! The two most important numbers are the %CPU and %MEM towards the right, as well as the COMMAND. This tells you how compute- and memory-intensive your program is. Right now, nothing&rsquo;s running so the numbers aren&rsquo;t very interesting, but just wait until we run something...</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/11603/ncbi-webinar</guid>
	<pubDate>Sun, 08 Jun 2014 02:47:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/11603/ncbi-webinar</link>
	<title><![CDATA[NCBI Webinar]]></title>
	<description><![CDATA[<p>In less than two weeks, NCBI will offer a webinar entitled "Introducing 3 NCBI Resources to Navigate Testing for Disease Linked Variants: MedGen, GTR and ClinVar". This webinar will delve into the lifecycle of genetic testing and teach attendees how to navigate the NIH Genetic Testing Registry, ClinVar, and MedGen resources. These resources can be used to prepare for clinical cases, access detailed information about orderable genetic tests, interpret test results, and more.</p><p>More at https://attendee.gotowebinar.com/register/8452228815737989634</p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12111/internship-program-with-arraygen-technolgies</guid>
  <pubDate>Sun, 22 Jun 2014 23:18:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship program with ArrayGen Technolgies]]></title>
  <description><![CDATA[
<p>Internship Program for Bioinformatics / Biotechnology Professionals Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis. Applications are accepted throughout the year. Accepted students will be listed on web with their schedules. Accepted students can attend our future workshops and trainings freely at the specified venue.</p>

<p>Interested candidates may email their resume along with a cover letter to careers@arraygen.com</p>

<p>Official website: http://www.arraygen.com/</p>
]]></description>
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  <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>
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<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>
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<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>
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	<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>
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  <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>
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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>
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