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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31064?offset=1400</link>
	<atom:link href="https://bioinformaticsonline.com/related/31064?offset=1400" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10841/ra-at-iisr-kozhikode</guid>
  <pubDate>Thu, 15 May 2014 10:08:09 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA at IISR Kozhikode]]></title>
  <description><![CDATA[
<p>INDIAN INSTITUTE OF SPICES RESEARCH<br />(Indian Council of Agricultural Research)<br />Marikunnu P.O., Kozhikode – 673 012, Kerala</p>

<p>Walk- in- Test cum Interview (based on test) for the selection of Research Associate</p>

<p>under the scheme “Distributed Information Sub Centre –DISC” &amp; Research Assistant under scheme “Phytophthora, Fusarium and Ralstonia diseases of Horticultural and Field Crops” will be held at this Institute as per details indicated below.</p>

<p>WALK -IN- TEST CUM INTERVIEW</p>

<p>Name of the post : Research Associate</p>

<p>Date of Interview : 21-05-2014 at 10.00 AM</p>

<p>No. of posts : One</p>

<p>Qualifications : a)Essential</p>

<p>Ph.D Degree in Bioinformatics OR :  Masters degree in Bioinformatics with a minimum of<br />60% marks or equivalent OGPA with at least two years research experience as evidenced from fellowship/ associateship/training/published papers etc.</p>

<p>b)Desirable: Experience in NGS data analysis.</p>

<p>Emoluments : Rs. 23,000/- per month + HRA (Masters Degree Holders)</p>

<p>Rs. 24,000/- per month + HRA (Ph.D Degree Holders)</p>

<p>Upper age limit : 40 years for Men &amp; 45 years for Women as on date of Interview (Upper Age limits are relaxable for SC, ST and OBC candidates as per Govt. of India norms (at present 5 years for SC/ST and 3 years for OBC)</p>

<p>Duration of Project : Till 31-03-2017.</p>

<p>Title of Assigment : Research Assistant (on contract basis)</p>

<p>No. of vacancy : One</p>

<p>Qualification : Essential : Post Graduation in Bioinformatics and  Minimum one year experience in NGS data analysis</p>

<p>Desirable : Experience in Perl/Python/R</p>

<p>Remuneration : Rs. 20,000/- per month (consolidated)</p>

<p>Scope of work :</p>

<p>1. Analysis of different file formats and their conversions.</p>

<p>2. Assessing the quality of data and filtering of raw reads.<br />3. Assembling the raw reads-de novo as well as reference  mapping.<br />4. Compression of aligned reads using Jam tools<br />5. RNA-seq. Analysis<br />6. Differential expression testing involving Normalization,  Statistical testing, heat map generation &amp; hierarchical  clustering<br />7. Annotating the assembled genome and geneet testing  and their validation<br />8. Metabolic pathway analysis<br />9. Comparative genomics<br />10. Setting up of genome browsers.</p>

<p>Period of Assigment : Initially for six months.</p>

<p>Date &amp; Venue of Interview : 21-05-2014 at IISR, Kozhikode at 10.00 AM</p>

<p>More at http://www.spices.res.in/pdf/disc-advtmnt.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</guid>
	<pubDate>Fri, 02 Feb 2018 13:25:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35429/list-of-visualization-tools-for-genome-alignments</link>
	<title><![CDATA[List of visualization tools for genome alignments]]></title>
	<description><![CDATA[<p><span>Genome</span><span>&nbsp;browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. But sometime, we need publication ready figure of genomes. Following are the list of genome alignment visualization tools, which could be useful for analysis and&nbsp;interpretation of results:</span></p><p>ABySS Explorer</p><p>Interactive Java application that uses a novel graph-based representation to display a sequence assembly and associated metadata</p><p>http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer</p><p>BamView</p><p>Genome browser and annotation tool that allows visualization of sequence features, next-generation sequencing (NGS) data and the results of analyses within the context of the sequence, and also its six-frame translation</p><p>http://www.sanger.ac.uk/resources/software/artemis/</p><p>DNannotator&nbsp;</p><p>Annotation web toolkit for regional genomic sequences</p><p>http://bioapp.psych.uic.edu/DNannotator.htm</p><p>JVM&nbsp;</p><p>Java Visual Mapping tool for NGS reads</p><p>http://www.springer.com/cda/content/document/cda_downloaddocument/9789401792448-c2.pdf?SGWID=0-0-45-1487072-p176815501</p><p>LookSeq&nbsp;</p><p>Web-based visualization of sequences derived from multiple sequencing technologies. Low- or high-depth read pileups and easy visualization of putative single nucleotide and structural variation</p><p>http://lookseq.sourceforge.net</p><p>MagicViewer&nbsp;</p><p>Visualization of short read alignment, identification of genetic variation and association with annotation information of a reference genome</p><p>http://bioinformatics.zj.cn/magicviewer/</p><p>MapView&nbsp;</p><p>Alignments of huge-scale single-end and pair-end short reads</p><p>http://omictools.com/mapview-s1367.html</p><p>MultiPipMaker</p><p>Computes alignments of similar regions in two DNA sequences. The resulting alignments are summarized with a &lsquo;percent identity plot&rsquo; (pip)</p><p>http://pipmaker.bx.psu.edu/pipmaker/</p><p>PileLineGUI&nbsp;</p><p>Handling genome position files in NGS studies</p><p>http://sing.ei.uvigo.es/pileline/pilelinegui.html</p><p>SAMtools tview&nbsp;</p><p>Simple and fast text alignment viewer; NGS compatible</p><p>http://www.htslib.org/</p><p>SEWAL</p><p>Uses a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run</p><p>http://www.sourceforge.net/projects/sewal</p><p>STAR&nbsp;</p><p>A web-based integrated solution to management and visualization of sequencing data</p><p>http://wanglab.ucsd.edu/star/browser</p><p>SVA&nbsp;</p><p>Software for annotating and visualizing sequenced human genomes</p><p>http://www.svaproject.org</p><p>Viewer (IGV)&nbsp;</p><p>Visualization of large heterogeneous datasets, providing a smooth and intuitive user experience at all levels of genome resolution</p><p>https://www.broadinstitute.org/igv/</p><p>ZOOM Lite&nbsp;</p><p>NGS data mapping and visualization software</p><p>http://bioinfor.com/zoom/lite/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11000/professorassociate-professor-assistant-professor-at-chettinad-academy-of-research-and-education</guid>
  <pubDate>Sat, 24 May 2014 00:00:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Professor/Associate Professor/ Assistant Professor at Chettinad Academy of Research and Education]]></title>
  <description><![CDATA[
<p>OPEN FACULTY POSITION</p>

<p>Chettinad Academy of Research and Education (CARE) invites applications from eligible and translational research-oriented candidates to the posts of Professor/Associate Professor/ Assistant Professor  Computational Biology, Bioinformatics, and Pharmaceutical Chemistry.</p>

<p>Emoluments: As per UGC norms (Adequate Compensation for Postdoctoral/Teaching experience)</p>

<p>Candidates fulfilling the eligibility criteria as per the UGC norms can send their full CV with copies of certificates and reference letters to the following address by post or by e-mail on or before 31st May 2014</p>

<p>The Registrar,<br />Chettinad Academy of Research and Education,<br />Chettinad Health City<br />Kelambakkam, Chennai 603 103<br />Tamil Nadu<br />T +91 (0)44 4741 1000<br />F +91 (0)44 4741 1011<br />Email: jobs @chettinadhealthcity.com</p>

<p>Advertisement: http://182.73.176.163/chc/ads2014.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36218/g-compass-a-comparative-genome-browser</guid>
	<pubDate>Thu, 12 Apr 2018 10:00:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36218/g-compass-a-comparative-genome-browser</link>
	<title><![CDATA[G-compass: a comparative genome browser]]></title>
	<description><![CDATA[<p><span>G-compass (</span><a href="http://www.h-invitational.jp/g-compass/" target="_top">http://www.h-invitational.jp/g-compass/</a><span>) is a comparative genome browser. It visualizes evolutionarily conserved genomic regions between human and other 12 vertebrates based on original genome alignments pursuing higher coverage (1,2). Annotations of human genes/transcripts and their ortholog information were derived from&nbsp;</span><a href="http://www.h-invitational.jp/hinv/ahg-db/index.jsp" target="_top">H-InvDB</a><span>&nbsp;and its subdatabase&nbsp;</span><a href="http://www.h-invitational.jp/evola/" target="_top">Evola</a><span>, respectively. G-compass is available for free of charge. [&nbsp;</span><a href="http://www.h-invitational.jp/g-compass/cgi-bin/gc_main.cgi?species_1=Hg18&amp;species_2=pt2&amp;strand_1=%2B&amp;strand_2=%2B&amp;from_win=main&amp;gen_str=2&amp;chr_1=01&amp;chr_2=01&amp;st_1=103804298&amp;ed_1=104204297&amp;st_2=105235351&amp;ed_2=105635350" target="_top">Sample</a><span>&nbsp;]</span></p><p>Address of the bookmark: <a href="http://www.h-invitational.jp/g-compass/" rel="nofollow">http://www.h-invitational.jp/g-compass/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/11107/the-minerva-research-group-for-bioinformatics</guid>
  <pubDate>Tue, 27 May 2014 15:48:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Minerva Research Group for Bioinformatics]]></title>
  <description><![CDATA[
<p>The focus of the bioinformatics group is to use computational approaches to gain an insight into genome evolution in primates.</p>

<p>http://www.eva.mpg.de/genetics/bioinformatics/overview.html?Fsize=0%2C%20%40%2F%27</p>

<p>Kelso Group<br />Department of Evolutionary Genetics<br />Max Planck Institute for Evolutionary Anthropology<br />Deutscher Platz 6<br />04103 Leipzig<br />Germany<br />Phone: +49 341 3550 500</p>

<p>Job: <br />http://www.eva.mpg.de/genetics/bioinformatics/jobs.html?Fsize=0%2C%2B%40</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36635/circlator-automated-circularization-of-genome-assemblies-using-long-sequencing-reads</guid>
	<pubDate>Tue, 15 May 2018 09:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36635/circlator-automated-circularization-of-genome-assemblies-using-long-sequencing-reads</link>
	<title><![CDATA[Circlator: automated circularization of genome assemblies using long sequencing reads]]></title>
	<description><![CDATA[A tool to circularize genome assemblies. The algorithm and benchmarks are described in the Genome Biology manuscript. 

Citation: "Circlator: automated circularization of genome assemblies using long sequencing reads", Hunt et al, Genome Biology 2015 Dec 29;16(1):294. doi: 10.1186/s13059-015-0849-0. PMID: 26714481.<p>Address of the bookmark: <a href="http://sanger-pathogens.github.io/circlator/" rel="nofollow">http://sanger-pathogens.github.io/circlator/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<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>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36890/price-paired-read-iterative-contig-extension-a-de-novo-genome-assembler-implemented-in-c</guid>
	<pubDate>Mon, 11 Jun 2018 03:08:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36890/price-paired-read-iterative-contig-extension-a-de-novo-genome-assembler-implemented-in-c</link>
	<title><![CDATA[PRICE (Paired-Read Iterative Contig Extension), a de novo genome assembler implemented in C++.]]></title>
	<description><![CDATA[We are pleased to release PRICE (Paired-Read Iterative Contig Extension), a de novo genome assembler implemented in C++. Its name describes the strategy that it implements for genome assembly: PRICE uses paired-read information to iteratively increase the size of existing contigs. Initially, those contigs can be individual reads from a subset of the paired-read dataset, non-paired reads from sequencing technologies that provide non-paired data, or contigs that were output from a prior run of PRICE or any other assembler.

http://derisilab.ucsf.edu/software/price/<p>Address of the bookmark: <a href="http://derisilab.ucsf.edu/software/price/" rel="nofollow">http://derisilab.ucsf.edu/software/price/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</guid>
	<pubDate>Sun, 01 Jun 2014 23:40:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</link>
	<title><![CDATA[Genomics and Personalized Medicine Breakthroughs]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/VAR-1vNc0TE" frameborder="0" allowfullscreen></iframe>http://bit.ly/e8QGzY Human genome mapping is now enabling a breakthrough in medical innovation -- personalized medicine. What does this mean for patients? We can now identify predispositions to disease, predict how we metabolize drugs, and figure out what kinds of treatments we may respond to, and even determine when a drug may give us an adverse reaction. All medical specialties benefit from human genome intelligence -- oncology saw the first impacts -- but advances are now being seen in cardiology, obstetrics and gynecology, pediatric diseases, gastroenterology, rheumatology, immunology and other areas. This video covers the areas that genetic medicine is impacting and where the future of genomic medicine is heading.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36960/links-scaffolder-bloomfilter-setting</guid>
	<pubDate>Fri, 15 Jun 2018 10:39:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36960/links-scaffolder-bloomfilter-setting</link>
	<title><![CDATA[LINKS scaffolder bloomfilter setting !]]></title>
	<description><![CDATA[
<p>➜  bin git:(master) ✗ ls -l<br />total 68<br />drwxrwxr-x 3 urbe urbe  4096 Jun 15 12:15 lib<br />-rwxrwxrwx 1 urbe urbe 65141 Jun 15 17:13 LINKS<br />➜  bin git:(master) ✗ pwd<br />/home/urbe/Tools/LINKS_1.8.6/bin</p>

<p>➜  bloomfilter git:(master) ✗ swig -Wall -c++ -perl5 BloomFilter.i<br />➜  bloomfilter git:(master) ✗ g++ -c BloomFilter_wrap.cxx -I/home/urbe/anaconda3/lib/perl5/5.22.0/x86_64-linux-thread-multi/CORE/ -fPIC -Dbool=char -O3<br />BloomFilter_wrap.cxx:1892:30: fatal error: ../BloomFilter.hpp: No such file or directory<br />compilation terminated.<br />➜  bloomfilter git:(master) ✗ cd swig <br />➜  swig git:(master) ✗ g++ -c BloomFilter_wrap.cxx -I/home/urbe/anaconda3/lib/perl5/5.22.0/x86_64-linux-thread-multi/CORE/ -fPIC -Dbool=char -O3<br />In file included from BloomFilter_wrap.cxx:1877:0:<br />../BloomFilter.hpp: In member function ‘void BloomFilter::loadHeader(FILE*)’:<br />../BloomFilter.hpp:141:59: warning: ignoring return value of ‘size_t fread(void*, size_t, size_t, FILE*)’, declared with attribute warn_unused_result [-Wunused-result]<br />         fread(&amp;header, sizeof(struct FileHeader), 1, file);<br />                                                           ^<br />➜  swig git:(master) ✗ g++ -Wall -shared BloomFilter_wrap.o -o BloomFilter.so -O3<br />➜  swig git:(master) ✗ cd ..<br />➜  bloomfilter git:(master) ✗ cd ..<br />➜  lib git:(master) ✗ cd ..<br />➜  bin git:(master) ✗ ./LINKS  <br />Usage: ./LINKS [v1.8.6]<br />-f  sequences to scaffold (Multi-FASTA format, required)<br />-s  file-of-filenames, full path to long sequence reads or MPET pairs [see below] (Multi-FASTA/fastq format, required)<br />-m  MPET reads (default -m 1 = yes, default = no, optional)<br />	! DO NOT SET IF NOT USING MPET. WHEN SET, LINKS WILL EXPECT A SPECIAL FORMAT UNDER -s<br />	! Paired MPET reads in their original outward orientation &lt;- -&gt; must be separated by ":"<br />	  &gt;template_name<br />	  ACGACACTATGCATAAGCAGACGAGCAGCGACGCAGCACG:ATATATAGCGCACGACGCAGCACAGCAGCAGACGAC<br />-d  distance between k-mer pairs (ie. target distances to re-scaffold on. default -d 4000, optional)<br />	Multiple distances are separated by comma. eg. -d 500,1000,2000,3000<br />-k  k-mer value (default -k 15, optional)<br />-t  step of sliding window when extracting k-mer pairs from long reads (default -t 2, optional)<br />	Multiple steps are separated by comma. eg. -t 10,5<br />-o  offset position for extracting k-mer pairs (default -o 0, optional)<br />-e  error (%) allowed on -d distance   e.g. -e 0.1  == distance +/- 10% (default -e 0.1, optional)<br />-l  minimum number of links (k-mer pairs) to compute scaffold (default -l 5, optional)<br />-a  maximum link ratio between two best contig pairs (default -a 0.3, optional)<br />	 *higher values lead to least accurate scaffolding*<br />-z  minimum contig length to consider for scaffolding (default -z 500, optional)<br />-b  base name for your output files (optional)<br />-r  Bloom filter input file for sequences supplied in -s (optional, if none provided will output to .bloom)<br />	 NOTE: BLOOM FILTER MUST BE DERIVED FROM THE SAME FILE SUPPLIED IN -f WITH SAME -k VALUE<br />	 IF YOU DO NOT SUPPLY A BLOOM FILTER, ONE WILL BE CREATED (.bloom)<br />-p  Bloom filter false positive rate (default -p 0.001, optional; increase to prevent memory allocation errors)<br />-x  Turn off Bloom filter functionality (-x 1 = yes, default = no, optional)<br />-v  Runs in verbose mode (-v 1 = yes, default = no, optional)</p>

<p>Error: Missing mandatory options -f and -s.</p>

<p>ERROR fixed</p>

<p>perl: symbol lookup error: /home/urbe/Tools/LINKS_new/bin/./lib/bloomfilter/swig/BloomFilter.so: undefined symbol: Perl_Gthr_key_ptr</p>
]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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