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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26906?offset=980</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5310/bergman-lab</guid>
  <pubDate>Thu, 03 Oct 2013 17:20:09 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bergman Lab]]></title>
  <description><![CDATA[
<p>Broad area of research:</p>

<p>Genome Annotation and Functional Genomics</p>

<p>Bergman Lab is actively engaged in the development and application of computational methods to improve the annotation of functional biological features in genome sequences.  Bergman Lab work focuses on improving annotation of non-protein-coding regions of the genome including conserved noncoding sequences (CNSs), cis-regulatory modules (CRMs), transcription factor binding sites (TFBSs), transposable elements (TEs) and noncoding RNA (ncRNA) genes. Current projects include improving the (i) annotation of TEs in the fly and yeast genomes, (ii) annotation of CRMs and TFBSs in the fly genome, and (iii) analysis of transposon knockout collections in flies. Research in this area is supported by the EC FP7 programme.</p>

<p>Genome and Molecular Evolution<br />Text and Data Mining</p>

<p>More @ http://bergmanlab.smith.man.ac.uk/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36603/learning-python-programming-a-bioinformatician-perspective</guid>
	<pubDate>Mon, 14 May 2018 16:33:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36603/learning-python-programming-a-bioinformatician-perspective</link>
	<title><![CDATA[Learning Python Programming - a bioinformatician perspective !]]></title>
	<description><![CDATA[<p>Python Programming&nbsp;is a general purpose programming language that is open source, flexible, powerful and easy to use. One of the most important features of python is its rich set of utilities and libraries for data processing and analytics tasks. In the current era of big biological data, python and biopython is getting more popularity due to its easy-to-use features which supports big data processing.</p><p>In this tutorial series article, I will explore features and packages of python which are widely used in the big data, NGS, and bioinformatics. I will also walk through a real biological example which shows NGS data processing with the help of python packages and programming.</p><p>Python has a couple of points to recommend it to biologists and scientists specifically:</p><ul>
<li>It's widely used in the scientific community</li>
<li>It has a couple of very well designed libraries for doing complex scientific computing (although we won't encounter them in this book)</li>
<li>It lend itself well to being integrated with other, existing tools</li>
<li>It has features which make it easy to manipulate strings of characters (for example, strings of DNA bases and protein amino acid residues, which we as biologists are particularly fond of)</li>
</ul><p>In general, following are some of the important features of python which makes it a perfect fit for rapid application development.</p><ul>
<li>Python is interpreted language so the program does not need to be compiled. Interpreter parses the program code and generates the output.</li>
<li>Python is dynamically typed, so the variables types are defined automatically.</li>
<li>Python is strongly typed. So the developers need to cast the type manually.</li>
<li>Less code and more use makes it more acceptable.</li>
<li>Python is portable, extendable and scalable.</li>
</ul><p>There are two major Python versions, Python 2 and Python 3. Python 2 and 3 are quite different. This tutorial uses Python 3, because it more semantically correct and supports newer features.</p><p>I will post tutorial on daily basis on this page. Check the sub-pages on right side.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</guid>
	<pubDate>Thu, 10 Oct 2013 11:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</link>
	<title><![CDATA[The anatomy of successful computational biology software]]></title>
	<description><![CDATA[<p>Creators of software widely used in computational biology discuss the factors that contributed to their success</p><p><em>Nature Biotechnology</em><span>&nbsp;spoke with Altschul and several other originators of computational biology software programs widely used today (</span><a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html#t1">Table 1</a><span>). The conversations explored what makes certain software tools successful, the unique challenges of developing them for biological research and how the field of computational biology, as a whole, can move research agendas forward. What follows is an edited compilation of interviews.</span></p><p>Detail @&nbsp;<a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html">http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html</a></p><p>News Source @ Nature</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates</guid>
	<pubDate>Thu, 16 May 2019 00:17:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates</link>
	<title><![CDATA[multiPhATE: bioinformatics pipeline for functional annotation of phage isolates]]></title>
	<description><![CDATA[<p><span>multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a&nbsp;</span><em>de novo</em><span>&nbsp;phage gene-calling algorithm and assigns putative functions to gene calls using protein-, virus-, and phage-centric databases.&nbsp;</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/carolzhou/multiPhATE" rel="nofollow">https://github.com/carolzhou/multiPhATE</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5663/network-analysis-indian-statistical-institute</guid>
  <pubDate>Wed, 16 Oct 2013 08:06:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Network Analysis @ Indian Statistical Institute]]></title>
  <description><![CDATA[
<p>Indian Statistical Institute Kolkata invites applications for the following posts</p>

<p>2013 Oct Advertisement from Indian Statistical Institute</p>

<p>Post: Network Analysis</p>

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

<p>Educational Qualifications:</p>

<p>Candidate should have passed BE/B.Tech Or Equivalent in Computer Science / Electrical Engineering / Electronics / Information Technology / Bioinformatics / Biotechnology with throughout first Class<br />Experience:</p>

<p>(details of experience required)<br />Pay Scale: INR Rs.16000-20000/-P.M.</p>

<p>Walk-In-Interview : 22 Oct 2013 at 10:30 AM</p>

<p>Download Official Notification:<br />http://www.isical.ac.in/JobApplicationFiles/MIU_0310201311433700.pdf</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5748/troyanskaya-lab</guid>
  <pubDate>Fri, 18 Oct 2013 10:57:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya  Lab]]></title>
  <description><![CDATA[
<p>In our research, we combine computational methods with an experimental component in a unified effort to develop comprehensive descriptions of genetic systems of cellular controls, including those whose malfunctioning becomes the basis of genetic disorders, such as cancer, and others whose failure might produce developmental defects in model systems.</p>

<p>Research Interest<br />Genomic Data Integration</p>

<p>Microarray Analysis</p>

<p>Gene and Protein Function Prediction</p>

<p>Detection and Analysis of Chromosomal Abnormalities and Functional Evolution</p>

<p>Integration of Computation and Experiments</p>

<p>Identification of Biological Networks and Pathways</p>

<p>Evaluation and Validation of Computational Predictions</p>

<p>Scalable Visualization-Based Data Analysis</p>

<p>More @ http://reducio.princeton.edu/cm/<br />PI page @ http://reducio.princeton.edu/cm/ogt</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40272/seq-a-high-performance-pythonic-language-for-bioinformatics</guid>
	<pubDate>Sat, 23 Nov 2019 08:58:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40272/seq-a-high-performance-pythonic-language-for-bioinformatics</link>
	<title><![CDATA[Seq: A high-performance, Pythonic language for bioinformatics]]></title>
	<description><![CDATA[<p>&nbsp;</p>
<p>Seq is a programming language for computational genomics and bioinformatics. With a Python-compatible syntax and a host of domain-specific features and optimizations, Seq makes writing high-performance genomics software as easy as writing Python code, and achieves performance comparable to (and in many cases better than) C/C++.</p>
<p>Learn more by following the&nbsp;<a href="https://github.com/seq-lang/seq/blob/master/docs/sphinx/tutorial.rst">tutorial</a>&nbsp;or from the&nbsp;<a href="https://github.com/seq-lang/seq/blob/master/docs/sphinx/cookbook.rst">cookbook</a>.</p><p>Address of the bookmark: <a href="https://seq-lang.org" rel="nofollow">https://seq-lang.org</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5957/assistant-professor-in-molecular-synthesis-for-drug-discovery-and-development-cbmr-lucknow</guid>
  <pubDate>Wed, 30 Oct 2013 06:42:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor in Molecular Synthesis for Drug Discovery and Development @ CBMR, Lucknow]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT FOR FACULTY POSITIONS AT CENTRE OF BIOMEDICAL RESEARCH (CBMR), LUCKNOW</p>

<p>Details of the Positions and Pay Structure:</p>

<p>03 Posts for Assistant Professor in Molecular Synthesis for Drug Discovery and Development</p>

<p>Essential Qualifications and Requirements:</p>

<p>1. PhD in Synthetic Organic Chemistry/Medicinal Chemistry with research publications in high quality international journals and first class grade at the preceding degree from recognised University/Institute in India or abroad with consistently good academic record.<br />2. Three Yrs of Post-doctoral experience in relevant area.<br />3. Below 35 Yrs of age at the time of application</p>

<p>Desirable Experience: Candidates having strong research background in organic synthesis, total synthesis of structurally complex and medicinally important natural products/drugs related to cancer, neurodegenerative diseases (neurotropically active molecules for Alzheimer's, Parkinson’s, dementia etc) and infectious diseases such as malaria, TB etc. will be preferred.</p>

<p>Interested candidates may apply with:</p>

<p>1. Filled up Application Form (download from CBMR Website: http://www.cbmr.res.in) along with the Cover Letter, Curriculum Vitae including academic record (Bachelor degree onwards), awards, honours, list of Publications and reprints of 5 best publications.<br />2. Proposed research plan (max 3-4 pages).<br />3. Names and address (with valid e-mail and Phone number) of at least 3 academic referees.<br />4. Online Payment Receipt with transaction reference no. of Rs. 1000/- (USD 100 or equivalent foreign currency) on following details.<br />Account Number: 30054847814 Name: Director, Centre of Biomedical Research<br />Bank: STATE BANK OF INDIA, SGPGI Campus Branch, LUCKNOW</p>

<p>IFSC Code: SBIN0007789<br />MICR No: 22602034</p>

<p>Applications can be sent by registered/speed post or by e-mail to the following address:</p>

<p>The Director,<br />Centre of Biomedical Research (CBMR),<br />Sanjay Gandhi PGI Campus,<br />Raebareli Road, Lucknow-226014<br />e-mail: cbmr.admin@cbmr.res.in,<br />gp.pandey@cbmr.res.in</p>

<p>More Info:</p>

<p>http://www.cbmr.res.in/career/Advertisement%20for%20the%20post%20of%20Professors%20and%20Assistant%20Professors.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40959/bioinformatics-related-group</guid>
	<pubDate>Sun, 09 Feb 2020 03:17:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40959/bioinformatics-related-group</link>
	<title><![CDATA[Bioinformatics related group]]></title>
	<description><![CDATA[<p>FaBI emerged from the respective groups of the four founding societies GI (German Informatics Society), DECHEMA (Society for Chemical Engineering and Biotechnology), GBM (Society for Biochemistry and Molecular Biology) and GDCh (German Chemical Society). In fall 2015, the GMDS (German Society for Medical Informatics, Biometry, and Epidemiology) joined FaBI. FaBI represents more than 750 members today and considers itself as a joint representation of interests of bioinformatics research in Germany and as an interlocutor for politics, economy, and society aiming at a strong informatics-based life science research.</p><p>Address of the bookmark: <a href="https://bioinformatik.de/en/bioinformatics-in-germany/research/research-groups.html" rel="nofollow">https://bioinformatik.de/en/bioinformatics-in-germany/research/research-groups.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24041/junior-bioinformatic-position</guid>
  <pubDate>Wed, 26 Aug 2015 05:35:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[Junior Bioinformatic position]]></title>
  <description><![CDATA[
<p>Junior Bioinformatic position in the laboratory of Inflammation and immunology in cardiovascular pathologies at Humanitas:</p>

<p>We are seeking a highly motivated young PhD student with strong interest in high throughput data analysis.<br />Detailed descriptions of our recent research activities may be found here:<br />http://www.humanitas-research.org/condorelli-gianluigi-md-phd/</p>

<p>Position is available starting from October/November. A probationary period of one month will be required.<br /> <br />Please send a CV along with a cover letter stating the reasons for applying and contact details of one or more referees to Dr. Paolo Kunderfranco (paolo.kunderfranco@humanitasresearch.it).</p>
]]></description>
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