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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31018?offset=1410</link>
	<atom:link href="https://bioinformaticsonline.com/related/31018?offset=1410" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43658/uniquekmer-generate-unique-kmers-for-every-contig-in-a-fasta-file</guid>
	<pubDate>Fri, 17 Dec 2021 00:08:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43658/uniquekmer-generate-unique-kmers-for-every-contig-in-a-fasta-file</link>
	<title><![CDATA[UniqueKmer: Generate unique KMERs for every contig in a FASTA file]]></title>
	<description><![CDATA[<p dir="auto">Generate unique k-mers for every contig in a FASTA file.</p>
<p dir="auto">Unique k-mer is consisted of k-mer keys (i.e. ATCGATCCTTAAGG) that are only presented in one contig, but not presented in any other contigs (for both forward and reverse strands).</p>
<p dir="auto">This tool accepts the input of a FASTA file consisting of many contigs, and extract unique k-mers for each contig.</p>
<p dir="auto">The output unique k-mer file and Genome file can be used for fastv:&nbsp;<a href="https://github.com/OpenGene/fastv">https://github.com/OpenGene/fastv</a>, which is an ultra-fast tool to identify and visualize microbial sequences from sequencing data.</p>
<p>https://github.com/OpenGene/UniqueKMER</p><p>Address of the bookmark: <a href="https://github.com/OpenGene/UniqueKMER" rel="nofollow">https://github.com/OpenGene/UniqueKMER</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21830/research-associate-bioinformatics-job-position-in-indian-agricultural-statistics-research-institute-iasri</guid>
  <pubDate>Tue, 31 Mar 2015 20:45:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate Bioinformatics job position in Indian Agricultural Statistics Research Institute (IASRI)]]></title>
  <description><![CDATA[
<p>Research Associate Bioinformatics job position in Indian Agricultural Statistics Research Institute (IASRI)</p>

<p>Qualification : Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent. Desirable: Knowledge of Statistical and Computational Genomics/ Proteomics/ Bioinformatics OR Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent with 1st Division or 60% marks or equivalent with at least two years of research experience. Desirable:Expertise on use of various software/ tool.</p>

<p>No.of Post: 2</p>

<p>Emoluments for RA: Consolidated Rs. 24000/- per month + 30% HRA for Ph.D holders and consolidated Rs. 23000/- per month + 30% HRA for Master Degree.</p>

<p>Age Limit : Age should not be more than 40 years for the post of Research associate (5 years relaxation for SC/ST/ women candidates) and 3 years for OBC candidates as on date of interview.<br />How to apply</p>

<p>Interested candidates are invited to appear for Walk-In interview at Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi -110012, along with filled in application form , all the original certificates from matriculation onwards, Ph.D. or M.Sc. certificate (as the case may be) must be produced at the time of interview in either original or provisional, Bio-Data, attested copies of all experience certificates, testimonials etc., one passport size photograph and one set of the self-attested photocopies of all the required certificates from matriculation onwards and an attested copy of recent passport size photograph pasted onto the application form. Walk-in interview will be held on 16th April, 2015 at 10:30 a.m.</p>

<p>Click Here for Job Details &amp; Application Form http://www.iasri.res.in/employment/employment.htm</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43909/human-complete-genome</guid>
	<pubDate>Wed, 06 Jul 2022 06:42:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43909/human-complete-genome</link>
	<title><![CDATA[Human Complete Genome]]></title>
	<description><![CDATA[<h1 dir="auto">Telomere-to-telomere consortium</h1>
<p dir="auto">We have sequenced the CHM13hTERT human cell line with a number of technologies. Human genomic DNA was extracted from the cultured cell line. As the DNA is native, modified bases will be preserved. The data includes 30x&nbsp;<a href="https://www.pacb.com/">PacBio</a>&nbsp;<a href="https://www.ncbi.nlm.nih.gov/sra/?term=SRX789768*+CHM13">HiFi</a>, 120x coverage of&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>, 70x&nbsp;<a href="https://www.pacb.com/">PacBio</a>&nbsp;CLR, 50x&nbsp;<a href="https://www.10xgenomics.com/">10X Genomics</a>, as well as&nbsp;<a href="https://bionanogenomics.com/technology/dls-technology/">BioNano DLS</a>&nbsp;and&nbsp;<a href="https://arimagenomics.com/kit/">Arima Genomics HiC</a>. Most raw data is available from this site, with the exception of the PacBio data which was generated by the University of Washington/PacBio and is available from&nbsp;<a href="https://www.ncbi.nlm.nih.gov/sra?linkname=bioproject_sra_all&amp;from_uid=269593">NCBI SRA</a>.</p>
<p dir="auto">A UCSC browser is available for&nbsp;<a href="https://genome.ucsc.edu/h/GCA_009914755.4">v2.0</a>&nbsp;(as well as legacy&nbsp;<a href="http://genome.ucsc.edu/cgi-bin/hgTracks?genome=t2t-chm13-v1.0&amp;hubUrl=http://t2t.gi.ucsc.edu/chm13/hub/hub.txt">v1.0</a>&nbsp;and&nbsp;<a href="http://genome.ucsc.edu/cgi-bin/hgTracks?genome=t2t-chm13-v1.1&amp;hubUrl=http://t2t.gi.ucsc.edu/chm13/hub/hub.txt">v1.1</a>&nbsp;versions). An interactive dotplot visualization of all genomic repeats is also available from&nbsp;<a href="https://resgen.io/paper-data/T2T-Nurk-et-al-2021/views/t2t-identity-v2">resgen.io</a>. Known issues identified in the assembly are tracked at&nbsp;<a href="https://github.com/marbl/CHM13-issues">CHM13 issues</a>.</p>
<p dir="auto">&nbsp;</p>
<p dir="auto">MORE at&nbsp;https://github.com/marbl/CHM13</p><p>Address of the bookmark: <a href="https://www.science.org/doi/10.1126/science.abj6987" rel="nofollow">https://www.science.org/doi/10.1126/science.abj6987</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/33629/list-of-universities-offering-bachelor-master-or-phd-bioinformatics-degree-in-malaysia</guid>
	<pubDate>Thu, 22 Jun 2017 01:34:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/33629/list-of-universities-offering-bachelor-master-or-phd-bioinformatics-degree-in-malaysia</link>
	<title><![CDATA[List of universities offering Bachelor,  Master or PhD bioinformatics degree in Malaysia]]></title>
	<description><![CDATA[<p>Bioinformatics is a newly emerging interdisciplinary research area, which may be defined as the ―interface between biological and computational sciences. Most of the Bioinformatics work that is done can be described as analyzing biological data, although a growing number of projects deal with the organization of biological information. The global Bioinformatics industry has grown at a double-digit growth rate in the past and is expected to follow the same pattern in the next four years. US remains the largest market in the world, but Asia-Pacific countries, particularly India and China, are witnessing the fastest growth and are anticipated to emerge as the dominating forces in future. The Comparison of Bioinformatics Industry between Malaysia, India and other countries&nbsp;are discussed in this&nbsp;<span>http://ijbssnet.com/journals/Vol.%202_No._10;_June_2011/11.pdf paper.</span></p><p>Bioinformatics is full of opportunities. The sector is poised to open new avenues for the other related sectors also. But the biggest opportunity area in the Bioinformatics market will be in the drug discovery sector. Reduction of both the cost and time taken to discover a new drug due to fast development in the Bioinformatics tools and software zone is also making drug discovery an attractive field to venture in. Malaysian bioinformatics growth and future are discuss in this https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2723929/ paper.&nbsp;Keeping all such inportance in mind, following universities in Malaysia offering bioinformatics cources:</p><p><strong>3 program(s) at AIMST University<strong>, Malaysia</strong></strong></p><p>Master of Science in Biotechnology (MSc) - Bioinformatics by Research</p><p>Master of Science (M.Sc) in Medical Microbiology (Bioinformatics) by Research</p><p>Doctor of Philosophy in Biotechnology (PhD) - Bioinformatics by Research</p><p>&nbsp;</p><p><strong>1 program(s) at INTI International University and Colleges<strong>, Malaysia</strong></strong></p><p>American Degree Transfer Program (Biosciences) in Bioinformatics</p><p>&nbsp;</p><p><strong>3 program(s) at Management and Science University (MSU)<strong>, Malaysia</strong></strong></p><p>Master in Bioinformatics (By Research)</p><p>PhD in Bioinformatics</p><p>Bachelor in Bioinformatics (Hons)</p><p>&nbsp;</p><p><strong>1 program(s) at Multimedia University (MMU)<strong>, Malaysia</strong></strong></p><p>Bachelor of Science (Honours) Bioinformatics</p><p>&nbsp;</p><p><strong>1 program(s) at Universiti Industri Selangor (UNISEL) Bestari Jaya Campus<strong>, Malaysia</strong></strong></p><p>Bachelor of Bioinformatics (Hons)</p><p>&nbsp;</p><p><strong>2 program(s) at Universiti Malaysia Sabah (UMS)<strong>, Malaysia</strong></strong></p><p>PhD - Doctor of Philosophy in Bioinformatics (By Research)</p><p>MSc - Master of Science in Bioinformatics (By Research)</p><p>&nbsp;</p><p><strong>6 program(s) at Universiti Putra Malaysia (UPM)<strong>, Malaysia</strong></strong></p><p>MSc - Master of Science in Bioinformatics by Research</p><p>Master of Science in Bioinformatics and System Biology by Research</p><p>Master of Science (M.Sc) in Bioinformatics and Systems Biology (With Thesis)</p><p>PhD - Doctor of Philosophy in Bioinformatics by Research</p><p>PhD - Doctor of Philosophy in Bioinformatics and Systems Biology (With Thesis)</p><p>PhD - Doctor of Philosophy in Bioinformatics and System Biology by Research</p><p>&nbsp;</p><p><strong>1 program(s) at Universiti Selangor (UNISEL)<strong>, Malaysia</strong></strong></p><p>Bachelor of Bioinformatics (Hons)</p><p>&nbsp;</p><p><strong>3 program(s) at Universiti Teknologi Malaysia (UTM)<strong>, Malaysia</strong></strong></p><p>M.Sc - Master of Science (Bioscience) in Bioinformatics Research Group (BIRG) By Research</p><p>PhD - Doctor of Philosophy (Bioscience) in Bioinformatics Research Group (BIRG) By Research</p><p>Bachelor of Computer Science (BioInformatics)</p><p>&nbsp;</p><p><strong>4 program(s) at University of Malaya (UM)<strong>, Malaysia</strong></strong></p><p>MSc - Master of Science in Bioinformatics by Research</p><p>Master in Bioinformatics by Coursework</p><p>PhD - Doctor of Philosophy in Bioinformatics by Research</p><p>Bachelor of Science (BSc) in Bioinformatics</p><p>&nbsp;</p><p><strong>3 program(s) at Perdana University<strong>, Malaysia</strong></strong></p><p>Master in Bioinformatics (By Research)</p><p>PhD in Bioinformatics</p><p>Bachelor in Bioinformatics (Hons)</p><p>&nbsp;</p><p><strong>3 program(s) at&nbsp;Monash University, Malaysia</strong></p><p>Master in Bioinformatics (By Research)</p><p>PhD in Bioinformatics</p><p>Bachelor in Bioinformatics (Hons)</p><p>&nbsp;</p><p><span>The real bioinformatics scope lies if there are research labs which work in this field. One has to take account of that. If so then try to get information of those labs and visit them to get a hang of the work they pursue. For detail Bioinformatics in Malaysia: Hope, Initiative, Effort, Reality, and Challenges are discussed in&nbsp;<span>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2723929/ paper.</span></span></p>]]></description>
	<dc:creator>sahabuddin</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44322/genome-context-viewer-gcv</guid>
	<pubDate>Sun, 21 May 2023 19:33:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44322/genome-context-viewer-gcv</link>
	<title><![CDATA[Genome Context Viewer (GCV)]]></title>
	<description><![CDATA[<p><span>The Genome Context Viewer (GCV) is a web-app that visualizes genomic context data provided by third party services. Specifically, it uses functional annotations as a unit of search and comparison. By adopting a common set of annotations, data-store operators can deploy federated instances of GCV, allowing users to compare genomes from different providers in a single interface.</span></p><p>Address of the bookmark: <a href="https://github.com/legumeinfo/gcv" rel="nofollow">https://github.com/legumeinfo/gcv</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21685/uiar-short-term-trainingfinal-year-dissertation-project-in-life-sciencesbioinformaticsbiotech</guid>
  <pubDate>Mon, 16 Mar 2015 23:56:25 -0500</pubDate>
  <link></link>
  <title><![CDATA[UIAR Short-Term Training/Final Year Dissertation Project in Life Sciences/Bioinformatics/Biotech]]></title>
  <description><![CDATA[
<p>Short-term training/Final year dissertation project</p>

<p>Candidates desirous of doing a short-term training / final year dissertation project for MSc (Life Sciences/Bioinformatics/Biotechnology or any science discipline) at UIAR Biophysics and Bioinformatics department may please drop an email atanju@iiar.res.in along with their resume.</p>

<p>Selected candidates will be further intimated. There will be a fees charged for doing the project at UIAR. The projects will be experimental or computational or involve both.</p>

<p>The training scope will be in the following areas but not limited to:</p>

<p>Bioinformatics analysis, Docking and Virtual screening, Molecular Dynamics simulation, Cloning, expression and purification of proteins, Biophysical and Biochemical characterisation of proteins, Crystallization and Structural Studies.</p>

<p>Advertisement: www.iiar.res.in/?q=node/450</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21894/bioinformatics-engineer-algorithm-development</guid>
  <pubDate>Wed, 01 Apr 2015 21:39:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Engineer -- Algorithm Development]]></title>
  <description><![CDATA[
<p>Centrillion Biosciences is a venture backed life sciences company located in Palo Alto, California. The company provides high quality genomic services to academic and industrial customers including top universities and research institutes. Centrillion Biosciences has an immediate opening for a full-time Bioinformatics Engineer. We're looking for an energetic, innovative, and motivated person who works well independently and on teams. The ideal candidate will have experience designing and implementing efficient algorithms to process large datasets. The role will involve collaborating with research scientists and other engineers, so strong communication skills are a must.</p>

<p>Job Description</p>

<p>• Work within a fast-paced, collaborative environment with small project teams working on a variety of tasks ranging from new product development to DNA data processing<br />• Collaborate with Centrillion research scientists in order to bridge the gap between the laboratory and the digital world<br />• Develop tools to enable research projects to cope with the enormous amounts of data produced by modern DNA sequencing experiments<br />• Build simulation algorithms to help guide and analyze research done in the lab<br />• Solve challenging engineering problems that require the development of innovative algorithms</p>

<p>Requirements</p>

<p>• Strong background in mathematics/statistics with a degree in a related field<br />• Strong analytical, coding, communication, and organizational skills<br />• Experience with algorithm development, simulations, and data analysis<br />• Proficiency in at least one modern programming language (like Python or Perl)<br />• Experience analyzing genetic and biological data sets (e.g., DNA data analysis and image analysis)<br />• Experience with machine learning and pattern recognition is preferred</p>

<p>Please submit your resume at https://www.centrillionbio.com/career/ to apply for this position.</p>
]]></description>
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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/22283/iihr-recruitment-2015-%E2%80%93-srf-project-asst-research-associate-posts</guid>
  <pubDate>Wed, 06 May 2015 06:13:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[IIHR Recruitment 2015 – SRF, Project Asst &amp; Research Associate Posts]]></title>
  <description><![CDATA[
<p>IIHR Recruitment 2015 – SRF, Project Asst &amp; Research Associate Posts: ICAR-Indian Institute of Horticultural Research (IIHR) has published a notification for the recruitment of Senior Research Fellow, Project Assistant and Research Associate vacancies on temporary basis. Eligible candidates may apply in prescribed application format on or before 15-05-2015. Other details like age, educational qualification, selection process, how to apply are given below…</p>

<p>IIHR Vacancy Details:<br />Total No. of Posts: 14<br />Name of the Post:<br />1. Senior Research Fellow: 12 Posts<br />2. Project Assistant: 01 Post<br />3. Research Associate: 01 Post</p>

<p>Age Limit: Candidates age limit is 40 years for men &amp; 45 years for women for RA post, 35 years for men &amp; 40 years for women for SRF post, 30 years for men &amp; 35 years for women for JRF post and 21 to 40 years for Other as on closing date of receipt of applications. Age relaxation is applicable as per rules.</p>

<p>Educational Qualification: Candidates should possess M.Sc (Ag) Plant Pathology or Microbiology or Biotechnology or Biochemistry or M.Tech (Ag) or Bioinformatics for SRF Posts, 10th class with experience in workshop (welding fitting) for Project Asst Post and M.Sc (Ag) Plant Pathology or M.Sc (Ag) Biotechnology or Ph.D in Plant Pathology or Agricultural Biotechnology for RA Post.</p>

<p>Selection Process: Candidates will be selected based on their performance in interview.</p>

<p>How to Apply: Eligible candidates may send their application in the prescribed format along with attested copies of relevant certificates and should mention name of PI/ Co-PI, Item No. of the Post &amp; name of the post clearly on the application as well as on the cover to the Concerned PI/ Co-PI, Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bengaluru-560089 on or before 15-05-2015 and attend the interview along with originals, two passport size photographs on 26 &amp; 27-05-2015 from 10:00 AM Onwards.</p>

<p>Important Dates:<br />Last Date for Receipt of Applications: 15-05-2015.<br />Date &amp; Time of Interview: 26 &amp; 27-05-2015 from 10:00 AM Onwards.<br />Venue: IIHR Campus.</p>

<p>More at http://www.iihr.ernet.in/content/srf-jrf-application-format</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</guid>
	<pubDate>Sat, 20 Sep 2025 09:34:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44902/hite-a-fast-and-accurate-dynamic-boundary-adjustment-approach-for-full-length-transposable-elements-detection-and-annotation-in-genome-assemblies</link>
	<title><![CDATA[HiTE: a fast and accurate dynamic boundary adjustment approach for full-length Transposable Elements detection and annotation in Genome Assemblies]]></title>
	<description><![CDATA[<p dir="auto"><code>HiTE</code>&nbsp;is a Python software that uses a dynamic boundary adjustment approach to detect and annotate full-length Transposable Elements in Genome Assemblies. In comparison to other tools, HiTE demonstrates superior performance in detecting a greater number of full-length TEs.</p>
<div dir="auto">
<h2 dir="auto">panHiTE</h2>
<a href="https://github.com/CSU-KangHu/HiTE#panhite"></a></div>
<p dir="auto">We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.</p>
<p dir="auto">For detailed instructions, please refer to the&nbsp;<a href="https://github.com/CSU-KangHu/HiTE/wiki/panHiTE-tutorial">panHiTE tutorial</a>.</p><p>Address of the bookmark: <a href="https://github.com/CSU-KangHu/HiTE" rel="nofollow">https://github.com/CSU-KangHu/HiTE</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

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