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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39606?offset=1160</link>
	<atom:link href="https://bioinformaticsonline.com/related/39606?offset=1160" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/35868/simpson-lab</guid>
  <pubDate>Tue, 06 Mar 2018 08:59:09 -0600</pubDate>
  <link></link>
  <title><![CDATA[Simpson Lab]]></title>
  <description><![CDATA[
<p>We are the Statistical Bioinformatics group in the Institute for Adaptive and Neural Computation in the School of Informatics at the University of Edinburgh. The group is led by Dr. Ian Simpson who is a Lecturer in Biological Informatics in the School of Informatics at Edinburgh University. Details to follow....</p>

<p>http://statbio.github.io</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/8972/bioinformaticcomputational-postdoc-at-south-dakota-state-university</guid>
  <pubDate>Wed, 12 Mar 2014 10:02:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatic/computational postdoc at South Dakota State University]]></title>
  <description><![CDATA[
<p>We seek an enthusiastic postdoctoral researcher to work with the Plant Science team within the Biochemical Spatio-temporal NeTwork Resource (BioSNTR). Bio-SNTR</p>

<p>is a state-funded virtual research center aimed at promoting imaging and informatics research infrastructure in South Dakota. BioSNTR research foci include analysis of large-scale genomics and imaging data, application of novel microscopy technologies to study signaling pathways, and identification of new compounds to manipulate signaling pathways.<br />Responsibilities: This person will be part of Plant Science team with research focus in bioinformatic and molecular network analyses of high throughput data (transcriptomic, proteomic, metabolomics, miRNA). The individual will be integrated into functional genomic projects encompassing grapevine dormancy and freezing tolerance (Fennell) and regulation of soybean nodulation (Subramanian). The successful candidate will perform computational analysis of high throughput, next-generation sequence data and possess the ability to use bioinformatics analytical tools on HPC clusters.</p>

<p> <br />Required Qualifications:<br />• Ph.D. in plant computational biology or bioinformatics.<br />• Experience in a high performance computing environment.<br />• Perl, Python and Java programming experience<br />• Data management and database development experience</p>

<p>Desired Qualifications:<br />• Parallel computing experience<br />• Experience working in a multidisciplinary environment</p>

<p>Contact Information<br />South Dakota State University<br />Plant Science<br />Anne Fennell<br />anne.fennell@sdstate.edu<br />Tel. Number: 605-688-6373<br />http://www.biosntr.org</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37618/snakemake%E2%80%94a-scalable-bioinformatics-workflow-engine</guid>
	<pubDate>Sun, 02 Sep 2018 16:32:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37618/snakemake%E2%80%94a-scalable-bioinformatics-workflow-engine</link>
	<title><![CDATA[Snakemake—a scalable bioinformatics workflow engine]]></title>
	<description><![CDATA[<p><span>Snakemake is a workflow engine that provides a readable Python-based workflow definition language and a powerful execution environment that scales from single-core workstations to compute clusters without modifying the workflow.&nbsp;</span></p><p>Address of the bookmark: <a href="https://bioconda.github.io/recipes/snakemake/README.html" rel="nofollow">https://bioconda.github.io/recipes/snakemake/README.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9029/syntax-for-secure-copy-scp</guid>
	<pubDate>Thu, 13 Mar 2014 17:01:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9029/syntax-for-secure-copy-scp</link>
	<title><![CDATA[Syntax for Secure Copy (scp)]]></title>
	<description><![CDATA[<div><p>In our day to day research activity, we need to securely copy our data from several to local computer and visa-versa. I am jotting down some of the commonly used SCP command for your future help. Hope you all will like it</p><p>What is Secure Copy?<br /><br />scp allows files to be copied to, from, or between different hosts. It uses ssh for data transfer and provides the same authentication and same level of security as ssh.</p><p><br />Examples</p><p><br /><strong>Copy the file "gene.txt" from a remote host to the local host</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp your_username@remotehost.edu:gene.txt /some/local/directory<br /><br /><strong>Copy the file "foobar.txt" from the local host to a remote host</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp gene.txt your_username@remotehost.edu:/some/remote/directory<br /><br /><strong>Copy the directory "chromosome" from the local host to a remote host's directory "bar"</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp -r chromosome your_username@remotehost.edu:/some/remote/directory/bar<br /><br /><strong>Copy the file "gene.txt" from remote host "rh1.edu" to remote host "rh2.edu"</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp your_username@rh1.edu:/some/remote/directory/gene.txt \<br />&nbsp;&nbsp;&nbsp; your_username@rh2.edu:/some/remote/directory/<br /><br /><strong>Copying the files "gene.txt" and "cancer.txt" from the local host to your home directory on the remote host</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp gene.txt cancer.txt your_username@remotehost.edu:~<br /><br /><strong>Copy the file "gene.txt" from the local host to a remote host using port 2264</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp -P 2264 gene.txt your_username@remotehost.edu:/some/remote/directory<br /><br /><strong>Copy multiple files from the remote host to your current directory on the local host</strong><br /><br />&nbsp;&nbsp;&nbsp; $ scp your_username@remotehost.edu:/some/remote/directory/\{a,b,c\} .<br /><br />&nbsp;&nbsp;&nbsp; $ scp your_username@remotehost.edu:~/\{gene.txt,cancer.txt\} .<br /><br /><strong>scp Performance</strong><br /><br />By default scp uses the Triple-DES cipher to encrypt the data being sent. Using the Blowfish cipher has been shown to increase speed. This can be done by using option -c blowfish in the command line.<br /><br />&nbsp;&nbsp;&nbsp; $ scp -c blowfish some_file your_username@remotehost.edu:~<br /><br />It is often suggested that the -C option for compression should also be used to increase speed. The effect of compression, however, will only significantly increase speed if your connection is very slow. Otherwise it may just be adding extra burden to the CPU. An example of using blowfish and compression:<br /><br />&nbsp;&nbsp;&nbsp; $ scp -c blowfish -C local_file your_username@remotehost.edu:~</p></div>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/39469/introduction-to-bioinformatics</guid>
	<pubDate>Wed, 05 Jun 2019 14:58:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/39469/introduction-to-bioinformatics</link>
	<title><![CDATA[Introduction to Bioinformatics]]></title>
	<description><![CDATA[<p><img src="https://edu.t-bio.info/wp-content/uploads/2017/07/Introduction-Course-Title-11.jpg" alt="Introduction to Bioinformatics Course" width="600" height="315.6" style="vertical-align: top; border: 0px; border: 0px;"></p><p>Introduction to bioinformatics is a course for biologists and clinicians that would like to learn more about the way bioinformatics is used in healthcare, biotech and pharmaceuitcal industry as well as basic research. The course covers many of the topics transformed by the emergence of big data and computational technologies. To learn more about the course, visit:&nbsp;<a href="https://edu.t-bio.info/course/introduction-bioinformatics/">https://edu.t-bio.info/course/introduction-bioinformatics/</a></p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
</item>

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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10391/research-associate-ra-at-iob</guid>
  <pubDate>Mon, 05 May 2014 08:38:54 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate (RA) at IOB]]></title>
  <description><![CDATA[
<p>Applications are invited for a post of Research Associate (RA) or Senior Research Fellow (SRF) in the ICMR project on "Integrated Analysis of Multi-omics Data in Human Gliomas".</p>

<p>We are looking for a motivated candidate for handling proteomic and/or transcriptomic and other data with a strong background in bioinformatics tools and database development. The project will include identification of novel peptides from mass spectrometry-based proteomic data.</p>

<p>Familiarity with statistical tools or wet lab experience will be an added advantage. The position is open for immediate appointment and available for two years. The applicant will be appointed as Research Associate or Senior Research Fellow based on qualifications as detailed below:</p>

<p>Research Associate: Ph.D. in Biological Science or Bioinformatics with relevant publications in peer reviewed journals. Familiarity with bioinformatics tools, database development, programming skills and proteomic and/or other omics data analysis. Salary will be as per ICMR rules and guidelines.</p>

<p>Senior Research Fellow: M.Sc./B.Tech. in any branch of biology/ biotechnology/bioinformatics, with minimum 2 years of research experience (essential). Familiarity with bioinformatics tools, database development, programming skills and proteomic data analysis. Salary will be as per ICMR rules and guidelines.</p>

<p>Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.</p>

<p>Interested candidates may send a Letter of Interest and CV by email to: ravi@ibioinformatics.org on or before May 15th, 2014.</p>

<p>Contact:<br />Dr. Ravi Sirdeshmukh<br />Distinguished Scientist &amp; Associate Director, IOB,<br />Principal Advisor MSMC/MSCTR</p>

<p>Advertisement: www.ibioinformatics.org/careers.php</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/40882/troyanskaya-lab</guid>
  <pubDate>Tue, 04 Feb 2020 06:40:36 -0600</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya Lab]]></title>
  <description><![CDATA[
<p>The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.</p>

<p>https://function.princeton.edu/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41394/ngsymposium-in-computational-biology</guid>
  <pubDate>Mon, 09 Mar 2020 06:00:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[NGSymposium in Computational Biology]]></title>
  <description><![CDATA[
<p>We have a great pleasure to invite you to the NGSymposium in Computational Biology to celebrate the 5th anniversary of the NGSchool Summer Schools. This international conference will make way for exchanging knowledge and experiences between experienced and early-stage researchers as well as bioinformaticians. The meeting will be held on 31.07 - 1.08.2020 in Warsaw. It will be a satellite event to the #NGSchool2020: Statistical Learning in Genomics. It will cover a wide range of topics from basic and applied biomedical sciences: bioinformatics, genomics, transcriptomics, computational biology, Machine Learning.</p>

<p>Registration of active participants will be open from February, 27 12 PM CET to April 17, 23:59 CET. In registration forms you will be asked for providing us with some basic information about yourself. You will also be able to submit your abstract. You can save your registration form after filling it partially and come back later to supply more data e.g. upload an abstract. Your registration will be completed only with the payment of the registration fee reaching our accounts - please make sure to transfer the money in advance!</p>

<p>Registration of passive participants will be open after closing of registration of active participants.</p>

<p>Details an registration: https://ngschool.eu/conference/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9701/postodoc-in-computationalsystems-biology-and-machine-learning</guid>
  <pubDate>Wed, 09 Apr 2014 20:47:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postodoc in Computational/Systems Biology and Machine Learning]]></title>
  <description><![CDATA[
<p>One profile of Computational/Systems Biology and Machine Learning at Postdoc level is needed at the Laboratory of Immunobiology of Neurological Disorders led by Cinthia Farina, Institute of Experimental Neurology, Ospedale San Raffaele, Milano. The projects of interest for this application involve research on translational bioinformatics in complex human disorders.<br /> <br />You have a  PhD in Computational Science, Bioinformatics,  or equivalent.<br /> <br />Especially relevant skills for the profile are:<br />1. In-depth understanding and implementation of methods and development of<br />algorithms for statistical and machine learning classification, clustering, predictive<br />modelling.<br />2. Experience on transcriptomics and clinical data analysis, in particular gene regulatory networks, protein interactomes, development of diagnostic tools.<br /> <br />3. Solid experience with data mining, bioinformatics programming and statistics for bioinformatics.<br />4. Flexibility and willing to work across multiple projects and technology in a rapidly evolving scientific context. <br /> <br />Candidates with programming/scripting experience are also welcome. In particular, proficiency in one or more mainstream programming languages (C, C++, Java, Python, Perl, etc.), together with the understanding of relational database design and SQL/DBMS systems (e.g. MySQL, PHP, Oracle).<br />Experience with the analysis of next-generation sequencing data is a plus.<br />Clear demonstration of experience in analysis and modelling of omics and clinical data must be provided.<br /> <br />Interested candidates should send to farina.cinthia@hsr.it:<br /> <br />1. CV (please show evidences of relevant titles, projects, courses, references, etc.)<br />2. One page with a list of research topics (i.e. ongoing projects)<br />3. earliest availability<br />4. 2-3 contact names</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</guid>
	<pubDate>Tue, 27 Oct 2020 19:42:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools</link>
	<title><![CDATA[Frequent parameters for bioinformatics tools !]]></title>
	<description><![CDATA[<div><div>Third party executable parameters and options.</div><div>&nbsp;</div><div>Trimmomatic</div><div>&nbsp;</div><div>&ldquo;ILLUMINACLIP:...:2:30:10&rdquo;</div><div>&ldquo;LEADING:15&rdquo;</div><div>&ldquo;TRAILING:15&rdquo;</div><div>&ldquo;SLIDINGWINDOW:4:20&rdquo;</div><div>&ldquo;MINLEN:20&rdquo;</div><div>&ldquo;TOPHRED33&rdquo;</div><div>&nbsp;</div><div>Filtlong</div><div>--min_length 500</div><div>--min_mean_q 85</div><div>--min_window_q 65</div><div>&nbsp;</div><div>FastQ Screen</div><div>--aligner bowtie2' (bwa for PacBio)</div><div>--subset 1000 (for PacBio)</div><div>&nbsp;</div><div>SPAdes</div><div>--careful</div><div>--disable-gzip-output</div><div>--cov-cutoff auto</div><div>--phred-offset 33</div><div>&nbsp;</div><div>HGAP</div><div>Pbalign.task_options.min_accuracy: 70</div><div>Pbalign.task_options.no_split_subreads: false</div><div>Genomic_consensus.task_options.min_confidence: 40</div><div>falcon_ns.task_options.HGAP_GenomeLength_str:</div><div>6000000</div><div>Pbcoretools.task_options.read_length: 0</div><div>Genomic_consensus.task_options.use_score: 0</div><div>Pbalign.task_options.min_length: 50</div><div>Pbalign.task_options.algorithm_options: --minMatch 12</div><div>--bestn 10 --minPctSimilarity 70.0</div><div>Pbalign.task_options.hit_policy: randombest</div><div>Pbcoretools.task_options.other_filters: rq &gt;= 0.7</div><div>Pbalign.task_options.concordant: false</div><div>Genomic_consensus.task_options.min_coverage: 5</div><div>falcon_ns.task_options.HGAP_SeedCoverage_str: 30</div><div>falcon_ns.task_options.HGAP_AggressiveAsm_bool: false</div><div>Genomic_consensus.task_options.algorithm: best</div><div>falcon_ns.task_options.HGAP_SeedLengthCutoff_str: -1</div><div>Genomic_consensus.task_options.diploid: false</div><div>&nbsp;</div><div>MeDuSa</div><div>-random 100</div><div>&nbsp;</div><div>Prokka</div><div>--usegenus</div><div>--force</div><div>--addgenes</div><div>--rfam</div><div>--rawproduct</div><div>&nbsp;</div><div>cmsearch (taxonomy, 16S)</div><div>--rfam</div><div>--noali</div><div>&nbsp;</div><div>blastn (taxonomy, 16S)</div><div>-evalue 1E-10</div><div>&nbsp;</div><div>blastn (MLST)</div><div>-ungapped</div></div><div><div>-dust no</div><div>-evalue 1E-20</div><div>-word_size 32</div><div>-culling_limit 2</div><div>-perc_identity 95</div><div>&nbsp;</div><div>blastp (VF)</div><div>-culling_limit 2</div><div>&nbsp;</div><div>RGI (ABR)</div><div>--input_type contig</div><div>&nbsp;</div><div>bowtie2 (mapping)</div><div>--sensitive</div><div>&nbsp;</div><div>minimap2 (mapping)</div><div>-a</div><div>-x map-ont</div><div>&nbsp;</div><div>samtools mpileup (SNP&nbsp;detection)</div><div>-uRI</div><div>&nbsp;</div><div>bcftools call (SNP detection)</div><div>--variants-only</div><div>--skip-variants indels</div><div>--output-type v</div><div>--ploidy 1</div><div>-c</div><div>&nbsp;</div><div>SNPsift filter (SNP detection)</div><div>"( QUAL &gt;= 30 ) &amp; (( na FILTER ) | (FILTER = 'PASS')) &amp;</div><div>( DP &gt;= 20 ) &amp; ( MQ &gt;= 20 )"</div><div>&nbsp;</div><div>SNPeff ann (SNP detection)</div><div>-nodownload</div><div>-no-intron</div><div>-no-downstream</div><div>-no SPLICE_SITE_REGION</div><div>-upDownStreamLen 250</div><div>&nbsp;</div><div>bcftools consensus</div><div>(phylogenetic tree)</div><div>--haplotype 1</div><div>&nbsp;</div><div>fasttreemp</div><div>-nt</div><div>-boot 100</div><div>&nbsp;</div><div>roary</div><div>-e</div><div>-n</div><div>-cd 100</div><div>-g 100000</div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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