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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26414?offset=1220</link>
	<atom:link href="https://bioinformaticsonline.com/related/26414?offset=1220" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/22047/binc-sample-question-paper</guid>
	<pubDate>Thu, 16 Apr 2015 09:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/22047/binc-sample-question-paper</link>
	<title><![CDATA[BINC Sample Question Paper !!!]]></title>
	<description><![CDATA[<p>BINC sample question paper round TWO.</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/22047" length="1621" type="text/plain" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44722/step-by-step-guide-to-running-genome-assembly</guid>
	<pubDate>Fri, 13 Dec 2024 11:35:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44722/step-by-step-guide-to-running-genome-assembly</link>
	<title><![CDATA[Step-by-Step Guide to Running Genome Assembly]]></title>
	<description><![CDATA[<p>Genome assembly is a critical process in bioinformatics, enabling the reconstruction of an organism's genome from short DNA sequence reads. Whether you&rsquo;re working on a new microbial genome or a complex eukaryotic organism, this guide will walk you through the steps of genome assembly using state-of-the-art tools and best practices.</p><h4><strong>What is Genome Assembly?</strong></h4><p>Genome assembly involves piecing together short DNA sequence reads generated by sequencing platforms (e.g., Illumina, PacBio, Oxford Nanopore) into longer, contiguous sequences called contigs. This can be performed as:</p><ul>
<li><strong>De Novo Assembly</strong>: Without a reference genome.</li>
<li><strong>Reference-Guided Assembly</strong>: Using a reference genome to guide the assembly process.</li>
</ul><h4><strong>Step 1: Preparing Your Data</strong></h4><p>Before starting the assembly, ensure that your raw sequencing data is high quality.</p><ol>
<li>
<p><strong>Input Data</strong></p>
<ul>
<li><strong>Short Reads</strong>: Illumina sequencing generates short, accurate reads ideal for scaffolding.</li>
<li><strong>Long Reads</strong>: PacBio and Nanopore sequencing provide long reads for resolving repetitive regions.</li>
</ul>
</li>
<li>
<p><strong>Quality Control (QC)</strong><br />Use tools like <strong>FastQC</strong> or <strong>MultiQC</strong> to assess the quality of your reads:</p>
<div>
<div dir="ltr"><code>fastqc reads.fastq multiqc . </code></div>
</div>
<p>Look for issues like low-quality bases, adapter contamination, or overrepresented sequences.</p>
</li>
<li>
<p><strong>Read Trimming and Filtering</strong><br />Trim low-quality bases and adapters using <strong>Trimmomatic</strong> or <strong>Cutadapt</strong>:</p>
<div>
<div dir="ltr"><code>trimmomatic PE reads_R1.fastq reads_R2.fastq trimmed_R1.fastq trimmed_R2.fastq \ ILLUMINACLIP:adapters.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:20 MINLEN:36 </code></div>
</div>
</li>
</ol><h4><strong>Step 2: Choosing an Assembly Strategy</strong></h4><p>Select an assembly strategy based on your data type:</p><ul>
<li>
<p><strong>Short-Read Assemblers</strong>:</p>
<ul>
<li>SPAdes: Popular for microbial genomes.</li>
<li>Velvet: Fast for smaller genomes.</li>
</ul>
</li>
<li>
<p><strong>Long-Read Assemblers</strong>:</p>
<ul>
<li>Canu: Ideal for long-read datasets.</li>
<li>Flye: Versatile for small and large genomes.</li>
</ul>
</li>
<li>
<p><strong>Hybrid Assemblers</strong>:</p>
<ul>
<li>MaSuRCA: Combines short and long reads.</li>
<li>Unicycler: Optimized for bacterial genomes.</li>
</ul>
</li>
</ul><h4><strong>Step 3: Running the Assembly</strong></h4><h5><strong>3.1. SPAdes (Short-Read Assembly)</strong></h5><p>SPAdes is an excellent choice for small genomes, such as bacteria.</p><div><div dir="ltr"><code>spades.py -1 trimmed_R1.fastq -2 trimmed_R2.fastq -o spades_output </code></div></div><p>The output includes assembled contigs (<code>contigs.fasta</code>) and scaffolds (<code>scaffolds.fasta</code>).</p><h5><strong>3.2. Canu (Long-Read Assembly)</strong></h5><p>Canu is designed for high-error long reads from PacBio or Nanopore.</p><div><div dir="ltr"><code>canu -p genome -d canu_output genomeSize=4.7m -nanopore-raw reads.fastq </code></div></div><p>The output will be in <code>canu_output/genome.contigs.fasta</code>.</p><h5><strong>3.3. Hybrid Assembly with Unicycler</strong></h5><p>Unicycler combines short and long reads for improved assemblies.</p><div><div dir="ltr"><code>unicycler -1 trimmed_R1.fastq -2 trimmed_R2.fastq -l long_reads.fastq -o unicycler_output </code></div></div><h4><strong>Step 4: Assessing Assembly Quality</strong></h4><p>After assembly, evaluate its quality using the following tools:</p><ol>
<li>
<p><strong>QUAST</strong><br />QUAST generates assembly statistics, such as N50, genome size, and GC content:</p>
<div>
<div dir="ltr"><code>quast contigs.fasta -o quast_output </code></div>
</div>
</li>
<li>
<p><strong>BUSCO</strong><br />BUSCO checks genome completeness by identifying conserved genes:</p>
<div>
<div dir="ltr"><code>busco -i contigs.fasta -o busco_output -l fungi_odb10 -m genome </code></div>
</div>
</li>
<li>
<p><strong>Assembly Graph Visualization</strong><br />Visualize assembly graphs with <strong>Bandage</strong>:</p>
<div>
<div dir="ltr"><code>Bandage load assembly_graph.gfa </code></div>
</div>
</li>
</ol><hr><h4><strong>Step 5: Post-Assembly Steps</strong></h4><ol>
<li>
<p><strong>Polishing</strong><br />Improve assembly accuracy using tools like <strong>Pilon</strong> (for short reads) or <strong>Racon</strong> (for long reads).</p>
<div>
<div dir="ltr"><code>racon long_reads.fasta mapped_reads.sam contigs.fasta &gt; polished_contigs.fasta </code></div>
</div>
</li>
<li>
<p><strong>Scaffolding</strong><br />Link contigs into scaffolds using tools like <strong>SSPACE</strong> or <strong>Opera-LG</strong> if required.</p>
</li>
<li>
<p><strong>Annotation</strong><br />Annotate the assembled genome using <strong>Prokka</strong> for prokaryotes or <strong>Maker</strong> for eukaryotes.</p>
<div>
<div dir="ltr"><code>prokka --outdir annotation_output --prefix genome contigs.fasta </code></div>
</div>
</li>
</ol><h4><strong>Step 6: Sharing and Archiving</strong></h4><ol>
<li>
<p><strong>Submit to Public Repositories</strong><br />Share your assembly in databases like <strong>NCBI GenBank</strong>, <strong>ENA</strong>, or <strong>DDBJ</strong>.</p>
</li>
<li>
<p><strong>Metadata Preparation</strong><br />Include detailed metadata for your submission, such as organism name, sequencing platform, and coverage.</p>
</li>
</ol><h4><strong>Best Practices</strong></h4><ul>
<li>Always perform quality checks at each stage to ensure data integrity.</li>
<li>Use multiple tools to cross-validate results when working with complex genomes.</li>
<li>Document parameters and software versions for reproducibility.</li>
</ul><h4><strong>Conclusion</strong></h4><p>Genome assembly is a powerful process that transforms raw sequencing data into a coherent representation of an organism&rsquo;s genome. By following this step-by-step guide, you can successfully assemble genomes and uncover valuable biological insights. Whether you&rsquo;re assembling a microbial genome or tackling the complexities of a eukaryotic genome, these tools and strategies will set you on the path to success.</p>]]></description>
	<dc:creator>Abhi</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22072/bioinformatics-jrfrasrf-position-at-indian-institute-of-science-education-and-research-iiser-kolkata-kolkata-west-bengal</guid>
  <pubDate>Fri, 17 Apr 2015 04:11:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/RA/SRF position at Indian Institute of Science Education and Research (IISER Kolkata) - Kolkata, West Bengal]]></title>
  <description><![CDATA[
<p>Research Position in Computational Biology in the group of Shree P. Pandey Positions available in the area of NGS data analysis, bioinformatics, plant genomics</p>

<p>Project Description: Projects involves high throughput analysis of data mostly generated by massively parallel sequencing (RNA-Seq and small-RNA-Seq), microarrays and related platforms. We are looking for highly motivated and bright individuals interested in high-throughput cutting-edge data analyses methods in genomics (computational positions). Available positions: Applications are invited from suitable candidates in both, the Max Planck India Partner Program and the CRP Wheat Program for openings at the levels:</p>

<p>Post Name-Qualification-Salary:<br />Project assistant – Master’s – Rs. 14000<br />Project fellow (junior data analyst) – Masters + research experience – Rs. 16000<br />Research fellow (senior data analyst) – Masters + adequate research experience/desirable skill sets – Rs. 22000<br />Research Associated – PhD (&lt; 1yr) /&gt; 1 yr experience – Rs. 28000 / Rs. 32000<br />Essential qualification: MSc/MTech/PhD (or other suitable qualification) in discipline related to bioinformatics, computational biology, computer application (or equivalent)/ ‘Advance Post-Graduate Diploma in Bioinformatics’. Proficiency in one of the programming languages or statistics (proficient in R for example) is compulsory.<br />Desirable qualification: 1. Programming experiences in at least one low level language such as C/C++ and one scripting language such as Perl/Python/PHP and knowledge of SQL/MySQL. 2. Substantial experience in the linux or other unix environments. 3. Experience of working in projects on Bioinformatics, Genetics or Biological application areas/Computational and Statistical analysis (e.g. using R or Matlab). Experience in the field of genomics (NGS, microarrays, genome annotation), database development and management, software development, systems and network biology (or related fields) will be preferred.<br />SELECTION PROCEDURE FOR INDIAN INSTITUTE OF SCIENCE EDUCATION AND RESEARCH (IISER KOLKATA) – RESEARCH ASSOCIATE &amp; MORE VACANCIES POST:</p>

<p>Candidates can apply on or before 30/04/2015<br />No Detailed information about the selection process is mentioned in the recruitment notification<br />HOW TO APPLY FOR RESEARCH ASSOCIATE &amp; MORE VACANCIES IN INDIAN INSTITUTE OF SCIENCE EDUCATION AND RESEARCH (IISER KOLKATA):</p>

<p>Applications should contain CV along with brief description (maximum 1 page) of research conducted (highlighting skills and experience) till now. Applications should be sent by email to Shree P. Pandey, Department of Biological Sciences, IISER-Kolkata, Mohanpur Campus, West Bengal within 2 weeks. Interviews will be scheduled within 10 days of closing of applications. E-mail: sppiiserkol@gmail.com, sppandey@iiserkol.ac.in<br />For more details visit: http://www.iiserkol.ac.in/~sppandey</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</guid>
	<pubDate>Tue, 04 Mar 2025 12:26:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</link>
	<title><![CDATA[Genomic architecture surrounding the fusion site of human chromosome 2]]></title>
	<description><![CDATA[<p>The article <strong>"Genomic Structure and Evolution of the Ancestral Chromosome Fusion Site in 2q13&ndash;2q14.1 and Paralogous Regions on Other Human Chromosomes (https://pmc.ncbi.nlm.nih.gov/articles/PMC187548/)"</strong> explores the genomic architecture surrounding the fusion site of human chromosome 2. This fusion event is a key evolutionary marker distinguishing humans from other great apes, as humans have 46 chromosomes while chimpanzees, gorillas, and orangutans possess 48. The fusion occurred through an end-to-end joining of two ancestral chromosomes, which remain separate in nonhuman primates.</p><h3><strong>Key Findings:</strong></h3><ol>
<li>
<p><strong>Chromosomal Fusion and Its Molecular Signature:</strong></p>
<ul>
<li>The fusion site is located at <strong>2q13&ndash;2q14.1</strong> and is characterized by <strong>degenerate telomeric sequences</strong> appearing interstitially, indicating the historical head-to-head joining of ancestral chromosomes.</li>
<li>Despite being a signature of a past fusion event, these telomeric repeats are no longer functional and have undergone sequence degradation over time.</li>
</ul>
</li>
<li>
<p><strong>Extensive Duplications in the Surrounding Genomic Region:</strong></p>
<ul>
<li>The study identifies <strong>large-scale segmental duplications</strong> flanking the fusion site, with several of these regions duplicated and scattered across multiple chromosomes.</li>
<li>These duplications are predominantly located in <strong>subtelomeric and pericentromeric regions</strong>, suggesting their role in genomic instability and chromosomal evolution.</li>
</ul>
</li>
<li>
<p><strong>Paralogous Regions and Their Evolutionary Relationships:</strong></p>
<ul>
<li>A <strong>168-kilobase (kb) segment</strong> near the fusion site has <strong>98%&ndash;99% sequence identity</strong> with three regions on <strong>chromosome 9 (9pter, 9p11.2, and 9q13)</strong>.</li>
<li>Another <strong>67-kb region distal to the fusion site</strong> shows a high degree of homology to sequences in <strong>chromosome 22qter</strong>.</li>
<li>Additionally, a <strong>100-kb segment</strong> exhibits <strong>96% sequence identity</strong> with a region in <strong>chromosome 2q11.2</strong>.</li>
</ul>
</li>
<li>
<p><strong>Comparative Genomics and Evolutionary Implications:</strong></p>
<ul>
<li>By comparing the duplicated sequences and their arrangement in primates, the researchers traced the order of duplication events leading to their present distribution.</li>
<li>The presence of specific repetitive elements within these duplicated segments serves as <strong>evolutionary markers</strong> that help infer their historical rearrangements.</li>
<li>Some of these <strong>duplicated regions are associated with chromosomal inversion breakpoints</strong>, potentially contributing to evolutionary changes in primates.</li>
<li>Recurrent <strong>structural rearrangements</strong> in these regions have been linked to human chromosomal disorders.</li>
</ul>
</li>
</ol><h3><strong>Conclusions and Implications:</strong></h3><ul>
<li>The findings provide valuable insights into <strong>the structural evolution of human chromosome 2</strong>, which played a crucial role in human speciation.</li>
<li>Understanding these <strong>segmental duplications</strong> and their evolutionary trajectories sheds light on <strong>genomic instability</strong>, which may contribute to <strong>human genetic diseases</strong>.</li>
<li>The study highlights how large-scale chromosomal rearrangements, such as fusion and duplication, have influenced the <strong>evolutionary divergence of humans</strong> from other primates.</li>
</ul><p>This research advances our understanding of <strong>human genome evolution</strong> and offers a foundation for studying the effects of <strong>structural variants in genetic disorders</strong>.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22235/project-fellow-bioinformatics-at-central-drug-research-institute</guid>
  <pubDate>Mon, 27 Apr 2015 20:15:45 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Fellow Bioinformatics at Central Drug Research Institute]]></title>
  <description><![CDATA[
<p>Project Fellow (Bioinformatics)<br />Central Drug Research Institute<br />Address: Chattar Manzil, M.G.Road, Kaisarbagh<br />Postal Code: 226001<br />City: Lucknow<br />State: Uttar Pradesh<br />Pay Scale: Rs.16,000/- (fixed) p.m.<br />Educational Requirements: M.Sc. in Bioinformatics with 55% marks for Gen. &amp; OBC and 50% marks for SC/ST candidates, Physically and Visually handicapped candidates<br />Experience Requirements: Experience in computer-assisted scientific research in the area of Drug Design including Bio- molecular modeling and simulation studies, Virtual screening, pharmacophore perception, QSAR etc. Familiarity with Linux/Unixbased computer systems and required to participate and contribute to the development and application of computational models for the design and discovery of novel molecules as inhibitors or chemical probes<br />Details will be available at: http://cdriindia.org/uploaded/advt_no01-2015.pdf</p>

<p>How To Apply: Eligible candidates required to report for the Interview at 9:00 A.M. sharp on 11-05-2015 (For Position Code No. 001 to 009) and 12-05-2015 (For Position Code No. 010 to 016). Candidates reporting after 10:00 A.M will not be allowed to attend the interview. Eligible candidates may appear before the Selection Committee for interview on the date and time mentioned above at CDRI, B.S. 10/1, Sector 10, Jankipuram Extension, Sitapur Road, Lucknow-226031. Eligible candidates must bring with them duly filled up application form (which can be downloaded from our website www.cdriindia.org), along with Original certificates as well as attested copies of certificates of examinations starting from matriculation, date of birth, caste certificate (in case of SC/ST/OBC) experience certificate, publication, if any and recent passport size photograph etc. Original documents are essential for verification of the particulars quoted by the candidate in the application form and candidate failed to produce original documents at the time of verification, shall not be allowed to attend the interview. Any request for relaxation in this regard shall not be entertained.<br />Detail of Interview: 11-05-2015<br />Age Limit: 28 Years</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34607/bbtools-user-guide</guid>
	<pubDate>Mon, 11 Dec 2017 06:37:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34607/bbtools-user-guide</link>
	<title><![CDATA[BBTools User Guide]]></title>
	<description><![CDATA[<p>The guides describe the function, syntax, and typical use-cases of the tools; for a complete list of parameters, run the tool&rsquo;s shellscript or open it with a text editor. Most tools do not currently have a guide, but each has shellscripts with basic usage information. The &ldquo;General Usage Guide&rdquo; gives shared background information covering usage of all tools.</p>
<p><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/installation-guide/">Installation</a></p>
<p><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/usage-guide/">General Usage Guide</a></p>
<p><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/data-preprocessing/">Data Preprocessing Guide</a></p>
<h2>Specific Tool Guides:</h2>
<ul>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbduk-guide/">BBDuk</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbmap-guide/">BBMap</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbmask-guide/">BBMask</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbmerge-guide/">BBMerge</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbnorm-guide/">BBNorm</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/calcuniqueness-guide/">CalcUniqueness</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/clumpify-guide/">Clumpify</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/dedupe-guide/">Dedupe</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/reformat-guide/">Reformat</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/repair-guide/">Repair</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/seal-guide/">Seal</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/split-nextera-guide/">Split Nextera</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/statistics-guide/">Statistics</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/tadpole-guide/">Tadpole</a></li>
<li><a href="http://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/taxonomy-guide/">Taxonomy</a></li>
</ul>
<p>https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/</p><p>Address of the bookmark: <a href="https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/" rel="nofollow">https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37592/benchmarking-perl-module</guid>
	<pubDate>Sat, 25 Aug 2018 11:40:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37592/benchmarking-perl-module</link>
	<title><![CDATA[Benchmarking Perl Module !]]></title>
	<description><![CDATA[<p>The benchmark module is a great tool to know the time the code takes to run. The output is usually in terms of CPU time. This module provides us with a way to optimize our code. With the advent of petascale computing and other multicore processor it is becoming a neccesity to know about the CPU time taken by our perl program.</p><p>This is the simple way to use the module</p><blockquote><p>Example1:</p><p>use Benchmark;</p><p>$first_time = Benchmark-&gt;new;</p><p>our code&hellip;&hellip;</p><p>$second_time = Benchmark-&gt;new;</p><p>$final_difference = timediff($first_time,$second_time);</p><p>print &ldquo;the code took, timestr($final_difference),&rdquo;\n&rdquo;;</p></blockquote><p>that was a very simple way to know the time diff , we can use it to know the time taken by some part of the code in the program.</p><blockquote><p>More sophisticated way:</p><p>use Benchmark;<br />sub first {</p><p>my(arguments) = @_;</p><p>}</p><p>timethese(100, { first =&gt; &lsquo;first_sub(arguments)&rsquo;});</p><p>The first argument to timethese is 100 (evaluate 100 times).</p></blockquote><p>Hope this very small tutorial with Benchmark will help people get started.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22297/appointment-of-two-traineeships-and-two-studentships-in-bioinformatics</guid>
  <pubDate>Fri, 08 May 2015 00:24:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Appointment of two traineeships and two studentships in Bioinformatics]]></title>
  <description><![CDATA[
<p>Applications are invited for the appointment of two traineeships and two studentships in Bioinformatics for a period of six months sponsored by Department of Biotechnology, Government of India in the Bioinformatics Sub-DIC, Saraswathy Thangavelu Centre, JNTBGRI, Puthenthope, Thiruvananthapuram 695 586. The required qualifications and other details are given below.</p>

<p>Position 1: Traineeship<br />Monthly fellowship (in rupee): 5,000/-<br />No. of vacancies: Two<br />Required Qualification: First Class M.Sc Bioinformatics/ Biotechnology/ Botany</p>

<p>Position 2: Studentship<br />Monthly fellowship (in rupee): 5,000/-<br />No. of vacancies: Two<br />Required Qualification: M.Phil/M.Tech Bioinformatics/ Biotechnology/ any branch of Life Science students for doing their thesis work in the area of Bioinformatics.</p>

<p>Age limit as on 1.1.2015, 28 years. Age relaxation will be provided for SC, ST, OBC candidates as per Govt. norms.</p>

<p>Interested candidates may appear for walk-in-interview on 15th May 2015 at 10.30 am at JNTBGRI, Palode, Thiruvananthapuram. The candidate should report to the Office at Palode before 10.00 am.</p>

<p>More at http://jntbgri.res.in/news/appointment-of-two-traineeships-and-two-studentships-in-bioinformatics/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/923/phylogenetic-for-bioinformatics</guid>
	<pubDate>Tue, 16 Jul 2013 03:50:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/923/phylogenetic-for-bioinformatics</link>
	<title><![CDATA[Phylogenetic for Bioinformatics]]></title>
	<description><![CDATA[<p>Biologists estimate that there are about 5 to 100 million species of organisms living on Earth today. Evidence from morphological, biochemical, and gene sequence data suggests that all organisms on Earth are genetically related, and the genealogical relationships of living things can be represented by a vast evolutionary tree, the Tree of Life. The Tree of Life then represents the phylogeny of organisms, i. e., the history of organismal lineages as they change through time.<br />Every living organism contains DNA, RNA, and proteins. Closely related organisms generally have a high degree of agreement in the molecular structure of these substances, while the molecules of organisms distantly related usually show a pattern of dissimilarity. Molecular phylogeny uses such data to build a "relationship tree" that shows the probable evolution of various organisms. Not until recent decades, however, has it been possible to isolate and identify these molecular structures.&nbsp;<br />phylogenetics is the study of evolutionary relatedness among various groups of organisms (for example, species or populations), which is discovered through molecular sequencing data and morphological data matrices. In other word, Phylogenetics, the science of phylogeny, is one part of the larger field of systematics, which also includes taxonomy. Taxonomy is the science of naming and classifying the diversity of organisms Molecular phylogeny is the use of the structure of molecules to gain information on an organism's evolutionary relationships. The result of a molecular phylogenetic analysis is expressed in a so-called phylogenetic tree.</p><p>The evolutionary connections between organisms are represented graphically through phylogenetic trees. Due to the fact that evolution takes place over long periods of time that cannot be observed directly, biologists must reconstruct phylogenies by inferring the evolutionary relationships among present-day organisms.&nbsp;<br />Application of the techniques that make this possible can be seen in the very limited field of human genetics, such as the ever more popular use of genetic testing to determine a child's paternity, as well as the emergence of a new branch of criminal forensics focused on genetic evidence.<br />The effect on traditional scientific classification schemes in the biological sciences has been dramatic as well. Work that was once immensely labor- and materials-intensive can now be done quickly and easily, leading to yet another source of information becoming available for systematic and taxonomic appraisal. This particular kind of data has become so popular that taxonomical schemes based solely on molecular data may be encountered. Proponents even claim that taxonomy was previously based on morphology alone, which of course is utter fable.<br /><br /><strong>For additional information on phylogenetics, see list of Phylogenetics Resources on the Internet.</strong></p><p>Phylogeny and Reconstructing Phylogenetic Trees:&nbsp;<a href="http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html"></a><a href="http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html">http://aleph0.clarku.edu/~djoyce/java/Phyltree/cover.html</a><br />the CBRG and Department of Statistics Phylogeny tutorial:&nbsp;<a href="http://www.compbio.ox.ac.uk/tutorials/phylogeny/"></a><a href="http://www.compbio.ox.ac.uk/tutorials/phylogeny/">http://www.compbio.ox.ac.uk/tutorials/phylogeny/</a><br />TUTORIAL: PHYLOGENETIC ANALYSIS USING PARSIMONY:<a href="http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html"></a><a href="http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html">http://home.cc.umanitoba.ca/~psgendb/GDE/phylogeny/parsimony/phylip.parsimony.html</a></p><p>PHYLIP:&nbsp;<a href="http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html"></a><a href="http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html">http://www.umanitoba.ca/afs/plant_science/psgendb/doc/Phylip/main.html</a><br />An Introduction to Molecular Phylogeny:&nbsp;<a href="http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf"></a><a href="http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf">http://bibiserv.techfak.uni-bielefeld.de/gcb04/tutorials/hoef-emden/GCB04Tut.pdf</a></p><p>How to make a phylogenetic tree:&nbsp;<a href="http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree"></a><a href="http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree">http://www.hiv.lanl.gov/content/sequence/TUTORIALS/TREE_TUTORIAL/Tree</a>tutorial.html<br />Phylogenetic Trees:&nbsp;<a href="http://cnx.org/content/m11052/latest/"></a><a href="http://cnx.org/content/m11052/latest/">http://cnx.org/content/m11052/latest/</a><br />Phylogeny by Ron Shamir:&nbsp;<a href="http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf"></a><a href="http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf">http://www.cs.tau.ac.il/~rshamir/algmb/01/scribe08/lec08.pdf</a><br />Introduction to Phylogeny:&nbsp;<a href="http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm"></a><a href="http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm">http://www.utm.edu/departments/cens/biology/rirwin/391/391Phylog.htm</a><br />Lecturer notes on Phylogeny:&nbsp;<a href="http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf"></a><a href="http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf">http://www.sbc.su.se/~bens/course_material/phylocourse1/lecture2.pdf</a><br />Principles and Practice of Phylogenetic Systematics:<a href="http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm"></a><a href="http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm">http://www.faculty.biol.ttu.edu/Strauss/Phylogenetics/LectureNotes.htm</a></p><p>Inferring phylogenetic trees:&nbsp;<a href="http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf"></a><a href="http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf">http://www.cis.hut.fi/Opinnot/T-61.6070/slides2008/pres_6070.pdf</a></p><p><strong>Lecture Notes</strong></p><p>Chapter 1 - The Diversity, Classification, and Evolution of Vertebrates:<a href="http://academic.emporia.edu/mooredwi/nathist/chap1.htm"></a><a href="http://academic.emporia.edu/mooredwi/nathist/chap1.htm">http://academic.emporia.edu/mooredwi/nathist/chap1.htm</a></p><p>Algorithms for Phylogenetic Reconstructions:<a href="http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf"></a><a href="http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf">http://lectures.molgen.mpg.de/Algorithmische_Bioinformatik_WS0405/phylogeny_script.pdf</a></p><p>Phylogeny.fr is a free, simple to use web service dedicated to reconstructing and analysing phylogenetic relationships between molecular sequences. Phylogeny.fr runs and connects various bioinformatics programs to reconstruct a robust phylogenetic tree from a set of sequences. For more detail :&nbsp;<a href="http://www.phylogeny.fr/version2_cgi/index.cgi"></a><a href="http://www.phylogeny.fr/version2_cgi/index.cgi">http://www.phylogeny.fr/version2_cgi/index.cgi</a></p><p>A Brief Tutorial on Phylogenetics<br /><a href="http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf"></a><a href="http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf">http://bioss.ac.uk/~dirk/talks/tutorial_phylogenetics.pdf</a></p><p>A Brief Tutorial on Phylogenetics Human Rabbit Chicken<br /><a href="http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf"></a><a href="http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf">http://bioss.ac.uk/~dirk/talks/psnup_tutorial_phylogenetics.pdf</a></p><p>Phylogenetic Tree Computation Tutorial Overview<br /><a href="http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf"></a><a href="http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf">http://pga.lbl.gov/Workshop/April2002/lectures/Olken.pdf</a></p><p>MrBayes: A program for the Bayesian inference of phylogeny<br /><a href="http://golab.unl.edu/teaching/SBseminar/manual.pdf"></a><a href="http://golab.unl.edu/teaching/SBseminar/manual.pdf">http://golab.unl.edu/teaching/SBseminar/manual.pdf</a></p><p><strong>Web sites providing software for the construction of phylogenetic trees</strong></p><ul>
<li><a href="http://www.mbio.ncsu.edu/BioEdit/bioedit.html">BioEdit</a></li>
</ul><ul>
<li><a href="http://www.dinofish.com/">Coelocanth-Fish Out of Time</a></li>
</ul><ul>
<li><a href="http://cbrg.inf.ethz.ch/">Computational Biochemistry Research Group</a></li>
</ul><ul>
<li><a href="http://www.geocities.com/RainForest/Vines/8695/software.html">Digital Taxonomy</a></li>
</ul><ul>
<li><a href="http://www.cladistics.org/education/hennig86.html">Hennig 86</a></li>
</ul><ul>
<li><a href="http://www.bioinformaticssolutions.com/">Hyperclean</a>&nbsp;from Bioinformatics Solutions, Inc.</li>
</ul><ul>
<li><a href="http://www.mun.ca/biology/scarr/Directory.html">Memorial University of Newfoundland</a></li>
</ul><ul>
<li><a href="http://morphbank.ebc.uu.se/mrbayes/">Mr. Bayes</a></li>
</ul><ul>
<li><a href="http://www.cladistics.com/about_nona.htm">NONA</a></li>
</ul><ul>
<li><a href="http://evolve.zoo.ox.ac.uk/">Oxford University Evolutionary Biology Group</a></li>
</ul><ul>
<li><a href="http://flatpebble.nceas.ucsb.edu/public/">Paleobiology Database</a></li>
</ul><ul>
<li><a href="http://paup.csit.fsu.edu/index.html">PAUP</a></li>
</ul><ul>
<li><a href="http://evolution.genetics.washington.edu/phylip.html">Phylip Homepage</a></li>
</ul><ul>
<li><a href="http://research.amnh.org/scicomp/projects/poy.php">Poy</a></li>
</ul><ul>
<li><a href="http://www.sinauer.com/">Sinauer Associates</a></li>
</ul><ul>
<li><a href="http://www.cladistics.org/downloads/webtnt.html">TNT</a>-Tree Analysis Using New Technology</li>
</ul><ul>
<li><a href="http://www.treebase.org/treebase/index.html">Tree Base</a></li>
</ul><ul>
<li><a href="http://www.treefinder.de/">Treefinder</a></li>
</ul><ul>
<li><a href="http://www.tree-puzzle.de/">Tree-Puzzle</a></li>
</ul><ul>
<li><a href="http://taxonomy.zoology.gla.ac.uk/rod/treeview.html">Tree View</a>-Taxonomy and Systematics Group at Glasgow</li>
</ul><ul>
<li><a href="http://evolution.genetics.washington.edu/phylip/software.html">Washington University</a>-List of Phylogeny Software</li>
</ul>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22393/narcis-fernandez-fuentes-lab</guid>
  <pubDate>Mon, 25 May 2015 07:30:00 -0500</pubDate>
  <link></link>
  <title><![CDATA[Narcis Fernandez-Fuentes Lab]]></title>
  <description><![CDATA[
<p>Welcome to our web-site compiling all the research-related activities of the group. Our research interests relate to a number of areas within Bioinformatics. We have a long-standing interest in protein structure prediction and structure-to-function relationships. We work in the study of biomolecular interactions, modeling of protein complexes, the study and characterization of protein-protein interactions, peptide design, modeling of genetic variation, structure-based protein design and different aspects of Plant Bioinformatics. Take a look at the our databases and servers and the list of publications for more information.</p>

<p>More at http://www.bioinsilico.org/</p>
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