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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42813?offset=60</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26303/maker</guid>
	<pubDate>Sun, 07 Feb 2016 15:59:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26303/maker</link>
	<title><![CDATA[MAKER]]></title>
	<description><![CDATA[<p>MAKER is a portable and easily configurable genome annotation pipeline.Its purpose is to allow smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. MAKER identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values.</p>
<p>More at http://www.yandell-lab.org/software/maker.html</p><p>Address of the bookmark: <a href="http://www.yandell-lab.org/software/maker.html" rel="nofollow">http://www.yandell-lab.org/software/maker.html</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26322/liftover</guid>
	<pubDate>Mon, 08 Feb 2016 15:45:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26322/liftover</link>
	<title><![CDATA[liftover]]></title>
	<description><![CDATA[<p><span>Convenient conversions between genome assemblie.&nbsp;The liftover package makes it easy to remap genomic coordinates to a different genome assembly. </span></p>
<p><span>More at https://github.com/aaronwolen/liftover<br></span></p>
<p><span>https://www.bioconductor.org/help/workflows/liftOver/</span></p><p>Address of the bookmark: <a href="https://github.com/aaronwolen/liftover" rel="nofollow">https://github.com/aaronwolen/liftover</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</guid>
	<pubDate>Mon, 29 Feb 2016 17:39:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn</link>
	<title><![CDATA[scikit-learn]]></title>
	<description><![CDATA[<p>Machine Learning in Python</p>
<p>Simple and efficient tools for data mining and data analysis<br> Accessible to everybody, and reusable in various contexts<br> Built on NumPy, SciPy, and matplotlib<br> Open source, commercially usable - BSD license</p>
<p>More at&nbsp;http://scikit-learn.org/stable/index.html</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://scikit-learn.org/stable/auto_examples/index.html" rel="nofollow">http://scikit-learn.org/stable/auto_examples/index.html</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44204/bioinformatics-training-collections</guid>
	<pubDate>Sun, 05 Mar 2023 23:01:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44204/bioinformatics-training-collections</link>
	<title><![CDATA[Bioinformatics Training Collections !]]></title>
	<description><![CDATA[<p>Useful list of bioinformatics training collections @&nbsp;https://github.com/sib-swiss/training-collection</p><p>Address of the bookmark: <a href="https://github.com/sib-swiss/training-collection" rel="nofollow">https://github.com/sib-swiss/training-collection</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35534/awk-for-bioinformatician-and-computational-biologist</guid>
	<pubDate>Tue, 06 Feb 2018 14:54:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35534/awk-for-bioinformatician-and-computational-biologist</link>
	<title><![CDATA[Awk for Bioinformatician and computational biologist]]></title>
	<description><![CDATA[<p>Awk is a programming language which allows easy manipulation of structured data and is mostly used for pattern scanning and processing. It searches one or more files to see if they contain lines that match with the specified patterns and then perform associated actions. The basic syntax is:</p><blockquote><p><br />awk '/pattern1/ {Actions}<br /> /pattern2/ {Actions}' file</p></blockquote><p><br />The working of Awk is as follows<br />Awk reads the input files one line at a time.<br />For each line, it matches with given pattern in the given order, if matches performs the corresponding action.<br />If no pattern matches, no action will be performed.<br />In the above syntax, either search pattern or action are optional, But not both.<br />If the search pattern is not given, then Awk performs the given actions for each line of the input.<br />If the action is not given, print all that lines that matches with the given patterns which is the default action.<br />Empty braces with out any action does nothing. It wont perform default printing operation.<br />Each statement in Actions should be delimited by semicolon.<br />Say you have data.tsv with the following contents:</p><p><br />$ cat data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />By default Awk prints every line from the file.</p><p><br />$ awk '{print;}' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />We print the line which matches the pattern contig3</p><p><br />$ awk '/contig3/' data/test.tsv<br />contig3 ACTTATATATATATA<br />Awk has number of builtin variables. For each record i.e line, it splits the record delimited by whitespace character by default and stores it in the $n variables. If the line has 5 words, it will be stored in $1, $2, $3, $4 and $5. $0 represents the whole line. NF is a builtin variable which represents the total number of fields in a record.</p><p><br />$ awk '{print $1","$2;}' data/test.tsv<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT</p><p>$ awk '{print $1","$NF;}' data/test.tsv<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT</p><p><br />Awk has two important patterns which are specified by the keyword called BEGIN and END. The syntax is as follows:</p><blockquote><p>BEGIN { Actions before reading the file}<br />{Actions for everyline in the file} <br />END { Actions after reading the file }</p></blockquote><p><br />For example,<br />$ awk 'BEGIN{print "Header,Sequence"}{print $1","$2;}END{print "-------"}' data/test.tsv<br />Header,Sequence<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT<br />------- <br />We can also use the concept of a conditional operator in print statement of the form print CONDITION ? PRINT_IF_TRUE_TEXT : PRINT_IF_FALSE_TEXT. For example, in the code below, we identify sequences with lengths &gt; 14:</p><p>$ awk '{print (length($2)&gt;14) ? $0"&gt;14" : $0"&lt;=14";}' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG&gt;14<br />contig2 ACTTTATATATT&lt;=14<br />contig3 ACTTATATATATATA&gt;14<br />contig4 ACTTATATATATATA&gt;14<br />contig5 ACTTTATATATT&lt;=14<br />We can also use 1 after the last block {} to print everything (1 is a shorthand notation for {print $0} which becomes {print} as without any argument print will print $0 by default), and within this block, we can change $0, for example to assign the first field to $0 for third line (NR==3), we can use:</p><p>$ awk 'NR==3{$0=$1}1' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT<br />You can have as many blocks as you want and they will be executed on each line in the order they appear, for example, if we want to print $1 three times (here we are using printf instead of print as the former doesn't put end-of-line character),</p><p>$ awk '{printf $1"\t"}{printf $1"\t"}{print $1}' data/test.tsv<br />contig1 contig1 contig1<br />contig2 contig2 contig2<br />contig3 contig3 contig3<br />contig4 contig4 contig4<br />contig5 contig5 contig5 <br />Although, we can also skip executing later blocks for a given line by using next keyword:</p><p>$ awk '{printf $1"\t"}NR==3{print "";next}{print $1}' data/test.tsv<br />contig1 contig1<br />contig2 contig2<br />contig3 <br />contig4 contig4<br />contig5 contig5</p><p>$ awk 'NR==3{print "";next}{printf $1"\t"}{print $1}' data/test.tsv<br />contig1 contig1<br />contig2 contig2</p><p>contig4 contig4<br />contig5 contig5<br />You can also use getline to load the contents of another file in addition to the one you are reading, for example, in the statement given below, the while loop will load each line from test.tsv into k until no more lines are to be read:</p><p>$ awk 'BEGIN{while((getline k &lt;"data/test.tsv")&gt;0) print "BEGIN:"k}{print}' data/test.tsv<br />BEGIN:contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />BEGIN:contig2 ACTTTATATATT<br />BEGIN:contig3 ACTTATATATATATA<br />BEGIN:contig4 ACTTATATATATATA<br />BEGIN:contig5 ACTTTATATATT<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />You can also store data in the memory with the syntax VARIABLE_NAME[KEY]=VALUE which you can later use through for (INDEX in VARIABLE_NAME) command:</p><p>$ awk '{i[$1]=1}END{for (j in i) print j"&lt;="i[j]}' data/test.tsv<br />contig1&lt;=1<br />contig2&lt;=1<br />contig3&lt;=1<br />contig4&lt;=1<br />contig5&lt;=1</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/36211/project-based-approach-to-improve-bioinformatics-education-with-skilled-and-meaningful-access-to-omics-data</guid>
	<pubDate>Wed, 11 Apr 2018 13:31:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/36211/project-based-approach-to-improve-bioinformatics-education-with-skilled-and-meaningful-access-to-omics-data</link>
	<title><![CDATA[Project-based approach to improve bioinformatics education with skilled and meaningful access to omics data]]></title>
	<description><![CDATA[<p>Pine Biotech has been collaborating with Loyola University of New Orleans on piloting a new approach to bioinformatics education using the intuitive and logic-drive bioinformatics platform T-BioInfo.</p><p>https://edu.t-bio.info/collaborative-model-bioinformatics-education-combining-biologically-inspired-bioinformatics-project-based-learning/</p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43323/biostarhandbook</guid>
	<pubDate>Fri, 27 Aug 2021 01:31:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43323/biostarhandbook</link>
	<title><![CDATA[biostarhandbook]]></title>
	<description><![CDATA[<p>Nice book collection for bioinformatician ... highly recommended.</p><p>Address of the bookmark: <a href="https://www.biostarhandbook.com/" rel="nofollow">https://www.biostarhandbook.com/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco</guid>
	<pubDate>Sat, 06 Feb 2021 13:31:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42811/bioinformatics-in-africa-part-4-morocco</link>
	<title><![CDATA[Bioinformatics in Africa: Part 4 - Morocco]]></title>
	<description><![CDATA[<p>Bioinformatics, in the UFR in Artificial Intelligence and Bioinformatics, deals with the management, the analysis, the modelling and the visualization of biological databases. Since the size of the databases is often exponential, the traditional algorithms are not very effective when seeking for a good computational solution.</p><p>To take care of this issue, many ways are opened to the researchers&nbsp;to&nbsp;improve&nbsp;the&nbsp;quality&nbsp;of&nbsp;the&nbsp;algorithms:</p><p>1. Usage of new information processing methods like artificial neuronal networks, genetic algorithms,&nbsp;etc. 2. Usage&nbsp;of&nbsp;Data&nbsp;mining&nbsp;&nbsp;to&nbsp;explore&nbsp;biochemical&nbsp;databases,<br />3. Usage of Machine learning on the biological examples to solve, for example, the problem of classification&nbsp;in&nbsp;Bioinformatics.</p><p>UFR&nbsp;offers&nbsp;in&nbsp;addition&nbsp;a&nbsp;doctoral&nbsp;training&nbsp;in&nbsp;Computer&nbsp;Science&nbsp;and&nbsp;Bioinformatics.</p><p>Doctoral&nbsp;module&nbsp;which&nbsp;includes:&nbsp;a&nbsp;Dipl&ocirc;me&nbsp;des&nbsp;Etudes&nbsp;Sup&eacute;rieures&nbsp;Approfondies&nbsp;(DESA)&nbsp; of&nbsp;two&nbsp;years;&nbsp;and&nbsp;a&nbsp;doctorate&nbsp;studies&nbsp;program&nbsp;with&nbsp;a&nbsp;national&nbsp;Ph.D.&nbsp;certification. Three&nbsp;specializations&nbsp;constitute&nbsp;the&nbsp;teaching&nbsp;trunk&nbsp;of&nbsp;the&nbsp;ENSAT:&nbsp;Computer&nbsp;engineering,&nbsp;Telecom&nbsp; engineering,&nbsp;and&nbsp;electronic&nbsp;systems&nbsp;engineering.</p><p>Research&nbsp;Interest&nbsp;and&nbsp;Activities:</p><p>The&nbsp;following&nbsp;are&nbsp;the&nbsp;present&nbsp;areas&nbsp;of&nbsp;research&nbsp;interest:</p><p>1. Machine&nbsp;Learning&nbsp;and&nbsp;Profile&nbsp;Gene&nbsp;Expression&nbsp;of&nbsp;Cancer<br />2. Predicting&nbsp;Protein&nbsp;structure <br />3. Hidden&nbsp;Markov&nbsp;Models&nbsp;(HMMs)&nbsp;and&nbsp;multiple&nbsp;alignments <br />4. Transformational&nbsp;Grammar&nbsp;for&nbsp;sequence&nbsp;modelling <br />5. Physical&nbsp;Mapping:&nbsp;STSs <br />6. Evolutionary&nbsp;Computation&nbsp;applied&nbsp;to&nbsp;Genomic&nbsp;and&nbsp;Proteomic <br />7. Predicate&nbsp;Logic&nbsp;and&nbsp;Protein&nbsp;Structure</p><p>Web&nbsp;site&nbsp;and&nbsp;links:</p><p>http://www.ensat.ac.ma/udiab http://www.pasteur.fr/pasteur/international/annonce_coursBioinfoannonce06_casa.pdf</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</guid>
	<pubDate>Wed, 20 Aug 2014 22:09:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</link>
	<title><![CDATA[Pimp your brain: Bioinformatics]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/KqelGy6Q8nE" frameborder="0" allowfullscreen></iframe>Jan Lisec from the Max Planck Institute of Molecular Plant Physiology explains, in this "pimp your brain" episode, what bioinformatics is and why bioinformatics is so important and indispensable for biological research.

In the video serial "Pimp your brain" scientists from the Max Planck Institute of Molecular Plant Physiology describe their research. More videos from the 'Pimp your brain' serial are available on www.youtube.com/playlist?list=PL-l9VItC9Gn2Ur2Xj6PTOAkjLUlVPbIOO

More videos are available on www.mpimp-golm.mpg.de]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19992/binc-examination-2015</guid>
	<pubDate>Mon, 29 Dec 2014 12:23:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19992/binc-examination-2015</link>
	<title><![CDATA[BINC examination 2015 !!!]]></title>
	<description><![CDATA[<p>Pondicherry University,Puducherry,on behalf of Department of Biotechnology, Government of India, will conduct the BINC examination in 2015. The objective of this examination is to certify bioinformatics professionals, trained formally as well as self-trained.Registration for BINC examination 2015 will open soon.</p><p>Pondicherry University Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely, Pune University, Pune; Anna University, Chennai; Calcatta University (WBUT) Kolkata; Institute of Bioinformatics &amp; Applied Biotechnology, Bangalore; North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad; University of Kerala, Thiruvananthapuram; Jawaharlal Nehru University, New Delhi and Assam Agricultural University, Guwahati.</p><p>In the BINC 2013 examination,17 candidates were certified. DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities. Note that the candidate must possess a postgraduate degree(or equivalent) &amp; meet the criteria of the institutes/universities in order to avail research fellowship. In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.<br /><br /></p><p>More at http://210.212.230.224:9999/BINC/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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