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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32633?offset=900</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44513/mike-an-ultrafast-assembly-and-alignment-free-approach-for-phylogenetic-tree-construction</guid>
	<pubDate>Mon, 08 Apr 2024 06:19:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44513/mike-an-ultrafast-assembly-and-alignment-free-approach-for-phylogenetic-tree-construction</link>
	<title><![CDATA[MIKE: an ultrafast, assembly-, and alignment-free approach for phylogenetic tree construction]]></title>
	<description><![CDATA[<p><span>MIKE (MinHash-based&nbsp;</span><em>k</em><span>-mer algorithm). This algorithm is designed for the swift calculation of the Jaccard coefficient directly from raw sequencing reads and enables the construction of phylogenetic trees based on the resultant Jaccard coefficient. Simulation results highlight the superior speed of MIKE compared to existing state-of-the-art methods. We used MIKE to reconstruct a phylogenetic tree, incorporating 238 yeast, 303&nbsp;</span><em>Zea</em><span>, 141&nbsp;</span><em>Ficus</em><span>, 67&nbsp;</span><em>Oryza</em><span>, and 43&nbsp;</span><em>Saccharum spontaneum</em><span>&nbsp;samples. MIKE demonstrated accurate performance across varying evolutionary scales, reproductive modes, and ploidy levels, proving itself as a powerful tool for phylogenetic tree construction.</span></p><p>Address of the bookmark: <a href="https://github.com/Argonum-Clever2/mike" rel="nofollow">https://github.com/Argonum-Clever2/mike</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30236/pyscaf</guid>
	<pubDate>Mon, 19 Dec 2016 14:20:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30236/pyscaf</link>
	<title><![CDATA[pyScaf]]></title>
	<description><![CDATA[<p>pyScaf orders contigs from genome assemblies utilising several types of information:</p>
<ul>
<li>paired-end (PE) and/or mate-pair libraries (<a href="https://github.com/lpryszcz/pyScaf#ngs-based-scaffolding">NGS-based mode</a>)</li>
<li>long reads (<a href="https://github.com/lpryszcz/pyScaf#scaffolding-based-on-long-reads">NGS-based mode</a>)</li>
<li>synteny to the genome of some related species (<a href="https://github.com/lpryszcz/pyScaf#reference-based-scaffolding">reference-based mode</a>)</li>
</ul>
<p>Scaffolding&nbsp;</p>
<p>In reference-based mode, pyScaf uses synteny to the genome of closely related species in order to order contigs and estimate distances between adjacent contigs.</p>
<p>Contigs are aligned globally (end-to-end) onto reference chromosomes, ignoring:</p>
<ul>
<li>matches not satisfying cut-offs (<code>--identity</code>&nbsp;and&nbsp;<code>--overlap</code>)</li>
<li>suboptimal matches (only best match of each query to reference is kept)</li>
<li>and removing overlapping matches on reference.</li>
</ul>
<p>In preliminary tests, pyScaf performed superbly on simulated heterozygous genomes based on&nbsp;<em>C. parapsilosis</em>&nbsp;(13 Mb; CANPA) and&nbsp;<em>A. thaliana</em>&nbsp;(119 Mb; ARATH) chromosomes, reconstructing correctly all chromosomes always for CANPA and nearly always for ARATH (<a href="https://www.dropbox.com/sh/bb7lwggo40xrwtc/AAAZ7pByVQQQ-WhUXZVeJaZVa/pyScaf?dl=0">Figures in dropbox</a>,&nbsp;<a href="https://docs.google.com/spreadsheets/d/1InBExy-qKDLj-upd8tlPItVSKc4mLepZjZxB31ii9OY/edit#gid=2036953672">CANPA table</a>,&nbsp;<a href="https://docs.google.com/spreadsheets/d/1InBExy-qKDLj-upd8tlPItVSKc4mLepZjZxB31ii9OY/edit#gid=1920757821">ARATH table</a>).<br>Runs took ~0.5 min for CANPA on&nbsp;<code>4 CPUs</code>&nbsp;and ~2 min for ARATH on&nbsp;<code>16 CPUs</code>.</p>
<p><span>Important remarks:</span></p>
<ul>
<li>Reduce your assembly before (fasta2homozygous.py) as any redundancy will likely break the synteny.</li>
<li>pyScaf works better with contigs than scaffolds, as scaffolds are often affected by mis-assemblies (no&nbsp;<em>de novo assembler</em>&nbsp;/ scaffolder is perfect...), which breaks synteny.</li>
<li>pyScaf works very well if divergence between reference genome and assembled contigs is below 20% at nucleotide level.</li>
<li>pyScaf deals with large rearrangements ie. deletions, insertion, inversions, translocations.&nbsp;<span>Note however, this is experimental implementation!</span></li>
<li>Consider closing gaps after scaffolding.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/lpryszcz/pyScaf" rel="nofollow">https://github.com/lpryszcz/pyScaf</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30334/postdoc-at-ubritishcolumbia-in-troutgenomics</guid>
  <pubDate>Thu, 22 Dec 2016 08:18:46 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoc at UBritishColumbia in TroutGenomics]]></title>
  <description><![CDATA[
<p>Landscape Genomics Postdoc at UBC A research team at the University of British Columbia’s Department of Zoology and Biodiversity Research Centre is seeking a postdoctoral researcher in landscape genetics of native rainbow trout (Oncorhynchus mykiss). </p>

<p>This project is part of a larger Genome Canada project on genetics and physiology of adaptation to climate change in rainbow trout, and the population genomics component is in the labs of Eric Taylor and Michael Whitlock. The landscape genomics component primarily involves whole genome sequencing approaches to understanding the genomic basis of adaptation to features of habitat, but also to provide insights into phylogeography and the influence of watershed structure on population subdivision in rainbow trout. A PhD in a related field with expertise in basic theory and bioinformatic analysis of population genomics data is required. </p>

<p>The position is available for one year with renewal for up to three additional years. Salary is $55,000 per year plus benefits. To apply, please send a brief cover letter summarizing your qualifications for the position, a CV, and the names, addresses, phone numbers and emails of three references. </p>

<p>Review of applications will begin January 16, 2017. Address application materials to etaylor@zoology.ubc.ca to whom any questions can also be addressed. etaylor@zoology.ubc.ca</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30459/prodigal-prokaryotic-dynamic-programming-genefinding-algorithm</guid>
	<pubDate>Thu, 29 Dec 2016 03:26:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30459/prodigal-prokaryotic-dynamic-programming-genefinding-algorithm</link>
	<title><![CDATA[Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm)]]></title>
	<description><![CDATA[<p><span>Prodigal (</span><strong>Pro</strong><span>karyotic&nbsp;</span><strong>Dy</strong><span>namic Programming&nbsp;</span><strong>G</strong><span>enefinding&nbsp;</span><strong>Al</strong><span>gorithm) is a microbial (bacterial and archaeal) gene finding program developed at Oak Ridge National Laboratory and the University of Tennessee. Key features of Prodigal include:</span></p>
<ul>
<li><strong>Speed</strong>: Prodigal is an extremely fast gene recognition tool (written in very vanilla C). It can analyze an entire microbial genome in 30 seconds or less.</li>
<li><strong>Accuracy</strong>: Prodigal is a highly accurate gene finder. It correctly locates the 3' end of every gene in the experimentally verified Ecogene data set (except those containing introns). It possesses a very sophisticated ribosomal binding site scoring system that enables it to locate the translation initiation site with great accuracy (96% of the 5' ends in the Ecogene data set are located correctly).</li>
<li><strong>Specificity</strong>: Prodigal's false positive rate compares favorably with other gene identification programs, and usually falls under 5%.</li>
<li><strong>GC-Content Indifferent</strong>: Prodigal performs well even in high GC genomes, with over a 90% perfect match (5'+3') to the&nbsp;<em>Pseudomonas aeruginosa</em>&nbsp;curated annotations.</li>
<li><strong>Metagenomic Version</strong>: Prodigal can run in metagenomic mode and analyze sequences even when the organism is unknown.</li>
<li><strong>Ease of Use</strong>: Prodigal can be run in one step on a single genomic sequence or on a draft genome containing many sequences. It does not need to be supplied with any knowledge of the organism, as it learns all the properties it needs to on its own.</li>
<li><strong>Open Source</strong>: Prodigal source code is freely available under the General Public License.</li>
</ul>
<p>&nbsp;</p>
<div style="text-align: center;"><strong>Download the latest version of Prodigal at&nbsp;<a href="http://github.com/hyattpd/prodigal/releases/">the Prodigal github page.</a></strong>&nbsp;<br>or&nbsp;<br><strong>Browse the&nbsp;<a href="http://github.com/hyattpd/prodigal/wiki">wiki documenation.</a></strong>&nbsp;</div><p>Address of the bookmark: <a href="http://prodigal.ornl.gov/" rel="nofollow">http://prodigal.ornl.gov/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/30654/source-code-and-pseudo-code</guid>
	<pubDate>Mon, 23 Jan 2017 10:17:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/30654/source-code-and-pseudo-code</link>
	<title><![CDATA[Source Code and Pseudo Code !!]]></title>
	<description><![CDATA[<p>An <span style="text-decoration: underline;">algorithm</span> is a procedure for solving a problem in terms of the actions to be executed and the order in which those actions are to be executed. An algorithm is merely the sequence of steps taken to solve a problem. The steps are normally "sequence," "selection, " "iteration," and a case-type statement.</p><p>In C, "sequence statements" are imperatives. The "selection" is the "if then else" statement, and the iteration is satisfied by a number of statements, such as the "while," " do," and the "for," while the case-type statement is satisfied by the "switch" statement.</p><hr><p><span style="text-decoration: underline;">Pseudocode</span> is an artificial and informal language that helps programmers develop algorithms. Pseudocode is a "text-based" detail (algorithmic) design tool.</p><p>The rules of Pseudocode are reasonably straightforward. All statements showing "dependency" are to be indented. These include while, do, for, if, switch. Examples below will illustrate this notion.</p><p><strong> GUIDE TO PSEUDOCODE LEVEL OF DETAIL: Given record/file descriptions, pseudocode should be created in sufficient detail so as to directly support the programming effort. It is the purpose of pseudocode to elaborate on the algorithmic detail and not just cite an abstraction. </strong></p><hr><p>Examples:</p><p>1.</p><pre>If student's grade is greater than or equal to 60
    Print "passed"
else
    Print "failed"  
endif
</pre><hr><p>2.</p><pre>  
Set total to zero
Set grade counter to one
While grade counter is less than or equal to ten
    Input the next grade
    Add the grade into the total
endwhile 
Set the class average to the total divided by ten
Print the class average.
</pre><hr><p>3.</p><pre>Initialize total to zero
Initialize counter to zero
Input the first grade
while the user has not as yet entered the sentinel
   add this grade into the running total 
   add one to the grade counter  
   input the next grade (possibly the sentinel)
endwhile

if the counter is not equal to zero
   set the average to the total divided by the counter
   print the average  
else
   print 'no grades were entered' 
endif 
</pre><hr><p>4.</p><pre>initialize passes to zero
initialize failures to zero
initialize student to one
while student counter is less than or equal to ten
    input the next exam result  
    if the student passed</pre><p>add one to passes else add one to failures add one to student counter endif endwhile print the number of passes print the number of failures if eight or more students passed print "raise tuition" endif</p><hr><h3><strong>5.</strong></h3><pre>Larger example:  

NOTE:  NEVER ANY DATA DECLARATIONS IN PSEUDOCODE

Print out appropriate heading and make it pretty
While not EOF do:
     Scan over blanks and white space until a char is found 
	(get first character on the line)
     set can't-be-ascending-flag to 0
     set consec cntr to 1
     set ascending cntr to 1
     putchar first char of string to screen
     set read character to hold character
     While next character read != blanks and white space
          putchar out on screen
          if new char = hold char + 1
               add 1 to consec cntr
               set hold char = new char
               continue
          endif
          if new char &gt;= hold char 
               if consec cntr &lt; 3 
                    set consec cntr to 1
               endif
               set hold char = new char
               continue
          endif
          if new char &lt; hold char
               if consec cntr &lt; 3
                    set consec cntr to 1
               endif
               set hold char = new char
               set can't be ascending flag to 1
               continue
           endif
     end while
     if consec cntr &gt;= 3 
          printf (Appropriate message 1 and skip a line)
          add 1 to consec total
     endif
     if  can't be ascending flag = 0
          printf (Appropriate message 2 and skip a line)
          add 1 to ascending total
     else
          printf (Sorry message and skip a line)
          add 1 to sorry total
     endif
end While
Print out totals:  Number of consecs, ascendings, and sorries.
Stop
</pre><p>Some Keywords That Should be Used And Additional Points</p><p>For looping and selection, The keywords that are to be used include Do While...EndDo; Do Until...Enddo; While .... Endwhile is acceptable. Also, Loop .... endloop is also VERY good and is language independent. Case...EndCase; If...Endif; Call ... with (parameters); Call; Return ....; Return; When;</p><p>Always use scope terminators for loops and iteration.</p><p>As verbs, use the words Generate, Compute, Process, etc. Words such as set, reset, increment, compute, calculate, add, sum, multiply, ... print, display, input, output, edit, test , etc. with careful indentation tend to foster desirable pseudocode. Also, using words such as Set and Initialize, when assigning values to variables is also desirable.</p><p>More on Formatting and Conventions in Pseudocoding</p><ul>
<li>INDENTATION in pseudocode should be identical to its implementation in a programming language. Try to indent at least four spaces.</li>
<li>As noted above, the pseudocode entries are to be cryptic, AND SHOULD NOT BE PROSE. NO SENTENCES.</li>
<li>No flower boxes (discussed ahead) in your pseudocode.</li>
<li>Do not include data declarations in your pseudocode.</li>
<li>But do cite variables that are initialized as part of their declarations. E.g. "initialize count to zero" is a good entry.<hr>Function Calls, Function Documentation, and Pseudocode</li>
<li>Calls to Functions should appear as:
<ul>     </ul>
</li>
<li>Returns in functions should appear as:
<ul> </ul>
</li>
<li>Function headers should appear as:
<ul>     </ul>
</li>
<li>Note that in C, arguments and parameters such as "fieldn" could be written: "pointer to fieldn ...."</li>
<li>Functions called with addresses should be written as:
<ul>         </ul>
</li>
<li>Function headers containing pointers should be indicated as:
<ul>        </ul>
</li>
<li>Returns in functions where a pointer is returned:
<ul>   </ul>
</li>
<li>It would not hurt the appearance of your pseudocode to draw a line or make your function header line "bold" in your pseudocode. Try to set off your functions.</li>
<li>Try to use scope terminators in your pseudocode and source code too. It really hels the readability of the text.<hr>Source Code</li>
<li>EVERY function should have a flowerbox PRECEDING IT. This flower box is to include the functions name, the main purpose of the function, parameters it is expecting (number and type), and the type of the data it returns. All of these listed items are to be on separate lines with spaces in between each explanatory item.</li>
<li>FORMAT of flowerbox should be
<p>&nbsp;</p>
<pre>	 ********************************************************
	 Function:   ( cryptic text describing single function
		     ....... (indented like this) 	
		     .......
	 Calls:      Start listing functions "this" function calls
		     Show these functions:  one per line, indented

	 Called by:  List of functions that calls "this" function
		     Show these functions:  one per line, indented.

	 Input Parameters:  list, if appropriate; else None
	 
	 Returns:    List, if appropriate.
	 ****************************************************************
</pre>
</li>
<li>INDENTATION is critically important in Source Code. Follow standard examples given in class. If in doubt, ASK. Always indent statements within IFs, FOR loops, WILLE loops, SWITCH statements, etc. a consistent number of spaces, such as four. Alternatively, use the tab key. One or two spaces is insufficient.</li>
<li>Use scope terminators at the end of if statements, for statements, while statements, and at the end of functions. It will make your program much more readable.
<p><strong> SPELLING ERRORS ARE NOT ACCEPTABLE </strong></p>
</li>
</ul>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30696/many-core-engine-mce-for-perl-example</guid>
	<pubDate>Tue, 31 Jan 2017 05:37:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30696/many-core-engine-mce-for-perl-example</link>
	<title><![CDATA[Many-Core Engine (MCE) for Perl example]]></title>
	<description><![CDATA[<p><span>MCE spawns a pool of workers and therefore does not fork a new process per each element of data. Instead, MCE follows a bank queuing model. Imagine the line being the data and bank-tellers the parallel workers. MCE enhances that model by adding the ability to chunk the next n elements from the input stream to the next available worker.</span></p>
<p>CORE MODULES</p>
<p>Three modules make up the core engine for MCE.</p>
<dl><dt id="MCE::Core"><a href="https://metacpan.org/pod/MCE#MCE::Core"><span></span></a><a></a><a href="https://metacpan.org/pod/distribution/MCE/lib/MCE/Core.pod">MCE::Core</a></dt><dd>
<p>Provides the Core API for Many-Core Engine. The various MCE options are described here.</p>
</dd><dt id="MCE::Signal"><a href="https://metacpan.org/pod/MCE#MCE::Signal"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Signal">MCE::Signal</a></dt><dd>
<p>Temporary directory creation, cleanup, and signal handling.</p>
</dd><dt id="MCE::Util"><a href="https://metacpan.org/pod/MCE#MCE::Util"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Util">MCE::Util</a></dt><dd>
<p>Utility functions for Many-Core Engine.</p>
</dd></dl>
<p><a href="https://metacpan.org/pod/MCE#MCE-EXTRAS"><span></span></a><a></a>MCE EXTRAS</p>
<p>There are 4 add-on modules for use with MCE.</p>
<dl><dt id="MCE::Candy"><a href="https://metacpan.org/pod/MCE#MCE::Candy"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Candy">MCE::Candy</a></dt><dd>
<p>Provides a collection of sugar methods and output iterators for preserving output order.</p>
</dd><dt id="MCE::Mutex"><a href="https://metacpan.org/pod/MCE#MCE::Mutex"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Mutex">MCE::Mutex</a></dt><dd>
<p>Provides a simple semaphore implementation supporting threads and processes.</p>
</dd><dt id="MCE::Queue"><a href="https://metacpan.org/pod/MCE#MCE::Queue"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Queue">MCE::Queue</a></dt><dd>
<p>Provides a hybrid queuing implementation for MCE supporting normal queues and priority queues from a single module. MCE::Queue exchanges data via the core engine to enable queuing to work for both children (spawned from fork) and threads.</p>
</dd><dt id="MCE::Relay"><a href="https://metacpan.org/pod/MCE#MCE::Relay"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Relay">MCE::Relay</a></dt><dd>
<p>Enables workers to receive and pass on information orderly with zero involvement by the manager process while running.</p>
</dd></dl>
<p><a href="https://metacpan.org/pod/MCE#MCE-MODELS"><span></span></a><a></a>MCE MODELS</p>
<p>The models take Many-Core Engine to a new level for ease of use. Two options (chunk_size and max_workers) are configured automatically as well as spawning and shutdown.</p>
<dl><dt id="MCE::Loop"><a href="https://metacpan.org/pod/MCE#MCE::Loop"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Loop">MCE::Loop</a></dt><dd>
<p>Provides a parallel loop utilizing MCE for building creative loops.</p>
</dd><dt id="MCE::Flow"><a href="https://metacpan.org/pod/MCE#MCE::Flow"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Flow">MCE::Flow</a></dt><dd>
<p>A parallel flow model for building creative applications. This makes use of user_tasks in MCE. The author has full control when utilizing this model. MCE::Flow is similar to MCE::Loop, but allows for multiple code blocks to run in parallel with a slight change to syntax.</p>
</dd><dt id="MCE::Grep"><a href="https://metacpan.org/pod/MCE#MCE::Grep"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Grep">MCE::Grep</a></dt><dd>
<p>Provides a parallel grep implementation similar to the native grep function.</p>
</dd><dt id="MCE::Map"><a href="https://metacpan.org/pod/MCE#MCE::Map"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Map">MCE::Map</a></dt><dd>
<p>Provides a parallel map model similar to the native map function.</p>
</dd><dt id="MCE::Step"><a href="https://metacpan.org/pod/MCE#MCE::Step"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Step">MCE::Step</a></dt><dd>
<p>Provides a parallel step implementation utilizing MCE::Queue between user tasks. MCE::Step is a spin off from MCE::Flow with a touch of MCE::Stream. This model, introduced in 1.506, allows one to pass data from one sub-task into the next transparently.</p>
</dd><dt id="MCE::Stream"><a href="https://metacpan.org/pod/MCE#MCE::Stream"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Stream">MCE::Stream</a></dt><dd>
<p>Provides an efficient parallel implementation for chaining multiple maps and greps together through user_tasks and MCE::Queue. Like with MCE::Flow, MCE::Stream can run multiple code blocks in parallel with a slight change to syntax from MCE::Map and MCE::Grep.</p>
</dd></dl>
<p><a href="https://metacpan.org/pod/MCE#MISCELLANEOUS"><span></span></a>MISCELLANEOUS</p>
<p>Miscellaneous additions included with the distribution.</p>
<dl><dt id="MCE::Examples"><a href="https://metacpan.org/pod/MCE#MCE::Examples"><span></span></a><a></a><a href="https://metacpan.org/pod/distribution/MCE/lib/MCE/Examples.pod">MCE::Examples</a></dt><dd>
<p>Describes various demonstrations for MCE including a Monte Carlo simulation.</p>
</dd><dt id="MCE::Subs"><a href="https://metacpan.org/pod/MCE#MCE::Subs"><span></span></a><a></a><a href="https://metacpan.org/pod/MCE::Subs">MCE::Subs</a></dt><dd>
<p>Exports functions mapped directly to MCE methods; e.g. mce_wid. The module allows 3 options; :manager, :worker, and :getter.</p>
</dd></dl>
<p><a href="https://metacpan.org/pod/MCE#REQUIREMENTS"><span></span></a>REQUIREMENTS</p>
<p>Perl 5.8.0 or later. PDL::IO::Storable is required in scripts running PDL.</p>
<p><a href="https://metacpan.org/pod/MCE#SOURCE-AND-FURTHER-READING"><span></span></a><a></a>SOURCE AND FURTHER READING</p>
<p>The source, cookbook, and examples are hosted at GitHub.</p>
<ul>
<li>
<p><a href="https://github.com/marioroy/mce-perl">https://github.com/marioroy/mce-perl</a></p>
</li>
<li>
<p><a href="https://github.com/marioroy/mce-cookbook">https://github.com/marioroy/mce-cookbook</a></p>
</li>
<li>
<p><a href="https://github.com/marioroy/mce-examples">https://github.com/marioroy/mce-examples</a></p>
</li>
</ul>
<p><a href="https://metacpan.org/pod/MCE#SEE-ALSO"><span></span></a><a></a>SEE ALSO</p>
<p><code>MCE::Shared</code>&nbsp;provides data sharing capabilities for&nbsp;<code>MCE</code>. It includes&nbsp;<code>MCE::Hobo</code>&nbsp;for running code asynchronously.</p>
<ul>
<li>
<p><a href="https://metacpan.org/pod/MCE::Shared">MCE::Shared</a></p>
</li>
<li>
<p><a href="https://metacpan.org/pod/MCE::Hobo">MCE::Hobo</a></p>
</li>
</ul><p>Address of the bookmark: <a href="https://github.com/marioroy/mce-examples" rel="nofollow">https://github.com/marioroy/mce-examples</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30825/open-positions-in-pasini%E2%80%99s-lab</guid>
  <pubDate>Sat, 04 Feb 2017 08:17:18 -0600</pubDate>
  <link></link>
  <title><![CDATA[Open Positions in Pasini’s lab]]></title>
  <description><![CDATA[
<p>Computational Biologists<br />Open to PhD-student and Post-doc candidates<br />We are looking for wet and computational biologists to work on an ERC funded project in our<br />laboratory located at the Department of Experimental Oncology of the European Institute of<br />Oncology in Milan (Italy). The project will focus on different aspects of the function of Polycomb<br />Group proteins and other chromatin modifying activities in relation to their role in regulating cellular<br />identity in the development of adult tissues.<br />The candidates will be in charge of computational analysis and data management related to the<br />project. She/he will directly interact with the wet scientists working in our laboratory while working<br />embedded in the community of computational biologists present at our institution. The work will<br />involve the analysis of sequencing data produced with cutting edge technologies to study gene<br />expression and chromatin environment including data produced on rare cell populations and single<br />cells. The applicants must have a good knowledge of programming in python/perl/java along with<br />strong statistical background and performing analysis in R platform. A biological background is<br />also recommended however it’s not mandatory for application.<br />Each applicant should submit a full CV (with a detailed description of her/his background,<br />expertise, achievements and publication records) together with a letter of intent and at least two<br />contacts for recommendations (for a post-doc position). Competitive salary will be offered based<br />on the experience of the candidate. Non Italian as well as Italian applicants that have been working<br />outside Italy (&gt;3yrs.) will have the opportunity to benefit of a full tax deduction for the first three<br />years of contract.<br />Applications should be submitted as single PDF to diego.pasini@ieo.it</p>

<p>Lab https://www.ieo.it/en/RESEARCH/People/Researchers/Pasini-Diego/</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30889/phd-program-in-computer-science-at-university-of-essex</guid>
  <pubDate>Sat, 11 Feb 2017 13:11:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[PhD program in Computer Science at University of Essex]]></title>
  <description><![CDATA[
<p>As part of the PhD program in Computer Science at University of Essex, I am looking for a PhD student in computational and synthetic biology.<br />The ideal candidate is interested in designing new biological design automation methods for genome scale projects and/or network modelling of genomic, transcriptomic and proteomic data.<br />Candidates interested in developing optimization algorithms for biological problems are encouraged to apply as well.<br />A summary of the research work in the lab can be found on o this page.</p>

<p>Candidates interested in the position should contact me in advance by email to: g.stracquadanio@essex.ac.uk</p>

<p>The deadline for the application is 28/02/2017; info about the application can be found on the Essex CSEE website.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30966/maftools</guid>
	<pubDate>Thu, 16 Feb 2017 11:16:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30966/maftools</link>
	<title><![CDATA[MafTools]]></title>
	<description><![CDATA[<p>maftools - An R package to summarize, analyze and visualize MAF files. <a href="https://github.com/PoisonAlien/maftools#introduction"></a>Introduction.</p>
<p>With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">resulting data</a> consisting of genetic variants is stored in the form of <a href="https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+%28MAF%29+Specification">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.</p>
<p>maftools is on <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f449.png" alt=":point_right:" width="20" height="20" style="border: 0px;"> <a href="http://biorxiv.org/content/early/2016/05/11/052662">bioRxiv</a> <img src="https://assets-cdn.github.com/images/icons/emoji/bowtie.png" alt=":bowtie:" title=":bowtie:" width="20" height="20" style="border: 0px; text-align: absmiddle;"></p>
<p>Please cite the below if you find this tool useful for you.</p>
<p>Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: <a href="http://dx.doi.org/10.1101/052662">http://dx.doi.org/10.1101/052662</a></p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31209/dial</guid>
	<pubDate>Wed, 01 Mar 2017 08:42:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31209/dial</link>
	<title><![CDATA[DIAL]]></title>
	<description><![CDATA[<p>A computational pipeline for identifying single-base substitutions between two closely related genomes without the help of a reference genome. DIAL works even when the depth of coverage is insufficient for de novo assembly, and it can be extended to determine small insertions/deletions. Our main motivation is to use this tool to survey the genetic diversity of endangered species as the identified sequence differences can be used to design genotyping arrays to assist in the species' management.</p>
<p>http://www.bx.psu.edu/~ratan/</p><p>Address of the bookmark: <a href="http://www.bx.psu.edu/miller_lab/" rel="nofollow">http://www.bx.psu.edu/miller_lab/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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