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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27090?offset=1080</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</guid>
	<pubDate>Tue, 08 Nov 2016 07:34:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29656/statistics-and-probability</link>
	<title><![CDATA[Statistics and probability]]></title>
	<description><![CDATA[<h3><span>Topics</span></h3>
<div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/displaying-describing-data">Displaying and describing data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/modeling-distributions-of-data">Modeling distributions of data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/describing-relationships-quantitative-data">Describing relationships in quantitative data</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/designing-studies">Designing studies</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/probability-library">Probability</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/random-variables-stats-library">Random variables</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/sampling-distributions-library">Sampling distributions</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/confidence-intervals-one-sample">Confidence intervals (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-one-sample">Significance tests (one sample)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/significance-tests-confidence-intervals-two-samples">Significance tests and confidence intervals (two samples)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/inference-categorical-data-chi-square-tests">Inference for categorical data (chi-square tests)</a></div>
<div><a href="https://www.khanacademy.org/math/statistics-probability/advanced-regression-inference-transforming">Advanced regression (inference and tran</a></div>
</div><p>Address of the bookmark: <a href="https://www.khanacademy.org/math/statistics-probability" rel="nofollow">https://www.khanacademy.org/math/statistics-probability</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41501/hicanu-accurate-assembly-of-segmental-duplications-satellites-and-allelic-variants-from-high-fidelity-long-reads</guid>
	<pubDate>Fri, 27 Mar 2020 22:49:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41501/hicanu-accurate-assembly-of-segmental-duplications-satellites-and-allelic-variants-from-high-fidelity-long-reads</link>
	<title><![CDATA[HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads]]></title>
	<description><![CDATA[<p><span>HiCanu, a significant modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering.&nbsp;</span></p>
<p>More at&nbsp;<a href="https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3?fbclid=IwAR2PaN4GLjvAZpWmCE2q0EWk2dtwY7wiKxVlXn9PPG7OBSP06PP2gcCrv3A">https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3</a></p><p>Address of the bookmark: <a href="https://github.com/marbl/canu" rel="nofollow">https://github.com/marbl/canu</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29693/bioistats-online-course</guid>
	<pubDate>Thu, 10 Nov 2016 04:22:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29693/bioistats-online-course</link>
	<title><![CDATA[Bioistats Online course]]></title>
	<description><![CDATA[<p><span>One of our primary focuses will be to develop an understanding of the various ways in which we can assign a probability to some chance event. We'll also learn the&nbsp;</span><strong>fundamental&nbsp;</strong><span><strong>properties of probability</strong>, investigate how probability behaves, and learn how to calculate the probability of a new chance event.</span></p>
<p><span>This book is handy understanding basic concepts.</span></p><p>Address of the bookmark: <a href="https://onlinecourses.science.psu.edu/stat414/node/287" rel="nofollow">https://onlinecourses.science.psu.edu/stat414/node/287</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29886/research-officer-at-national-tea-research-foundation</guid>
  <pubDate>Fri, 18 Nov 2016 04:19:24 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Officer at National Tea Research Foundation]]></title>
  <description><![CDATA[
<p>National Tea Research Foundation (NTRF) a registered body, requires qualified and experienced agricultural research scientist for contractual appointment as per details below :</p>

<p>Post Research Officer, NTRF, Kolkata</p>

<p>Essential Post Graduate degree in Life Science having special paper in Bioinformatics. Post Graduate degree in Bioinformatics.</p>

<p>Desirable Ph. D. in the area of computational biology or bioinformatics.</p>

<p>Job Experience Work experience on database development, capable to work independently and efficient in bioinformatics related project.</p>

<p>Job Responsibility</p>

<p>To develop database on various aspects of tea research.</p>

<p>Screening of the In-house projects of NTRF at the preliminary level.</p>

<p>Review and evaluation of In-house projects of NTRF. Technical monitoring of the In-house projects of NTRF.</p>

<p>Reviewing the final technical report of the In-house projects of NTRF.</p>

<p>Putting-up of same proposals for taking approval and sanction of the competent authority.</p>

<p>Physical and technical verification of the In-house projects of NTRF.</p>

<p>To assist in organizing seminars / workshops / meetings etc.</p>

<p>Interested candidate may appear for walk-in Interview on 17 th November, 2016</p>

<p>More Info :</p>

<p>http://www.teaboard.gov.in/pdf/Recruitment_for_the_post_of_Research_Officer_pdf7538.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</guid>
	<pubDate>Fri, 05 Feb 2021 21:22:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</link>
	<title><![CDATA[GraphUnzip: Phases an assembly graph using Hi-C data and/or long reads.]]></title>
	<description><![CDATA[<p>GraphUnzip, a fast, memory-efficient and accurate tool to unzip assembly graphs into their constituent haplotypes using long reads and/or Hi-C data. As GraphUnzip only connects sequences in the assembly graph that already had a potential link based on overlaps, it yields high-quality gap-less supercontigs. To demonstrate the efficiency of GraphUnzip, we tested it on a simulated diploid Escherichia coli genome, and on two real datasets for the genomes of the rotifer Adineta vaga and the potato Solanum tuberosum. In all cases, GraphUnzip yielded highly continuous phased assemblies.</p>
<p>https://www.biorxiv.org/content/biorxiv/early/2021/02/01/2021.01.29.428779.full.pdf</p><p>Address of the bookmark: <a href="https://github.com/nadegeguiglielmoni/GraphUnzip" rel="nofollow">https://github.com/nadegeguiglielmoni/GraphUnzip</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29992/spines</guid>
	<pubDate>Mon, 28 Nov 2016 05:33:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29992/spines</link>
	<title><![CDATA[Spines]]></title>
	<description><![CDATA[<p><a href="https://www.broadinstitute.org/ftp/distribution/software/spines/"><em>Spines</em></a>&nbsp;is a collection of software tools, developed and used by the Vertebrate Genome Biology Group at the Broad Institute. It provides basic data structures for efficient data manipulation (mostly genomic sequences, alignments, variation etc.), as well as specialized tool sets for various analyses. It also features three sequence alignment packages:&nbsp;<em>Satsuma,</em>&nbsp;a highly parallelized program for high-sensitivity, genome-wide synteny;&nbsp;<em>Papaya,</em>&nbsp;an all-purpose alignment tool for less diverged sequences; and&nbsp;<em>SLAP,</em>&nbsp;a context-sensitive local aligner for diverged sequences with large gaps.</p>
<p>Access&nbsp;<em>Spines</em>&nbsp;<a href="https://www.broadinstitute.org/ftp/distribution/software/spines/">here</a>.</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/genome-sequencing-and-analysis/spines" rel="nofollow">https://www.broadinstitute.org/genome-sequencing-and-analysis/spines</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30018/bipype</guid>
	<pubDate>Thu, 01 Dec 2016 08:47:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30018/bipype</link>
	<title><![CDATA[bipype]]></title>
	<description><![CDATA[<p><span>Bipype is a very useful program, which prepare a lot of types of bioinformatics analyses. There are three input options: amplicons, WGS (whole genome sequences) and metatranscriptomic data. If amplicons are input data, then bipype does reconstruction and pairs merging. After that biodiversity is searching. There are two types of searching depending on the amplicons types (ITS or 16S). If WGS are chosen, then bipype finds the SA coordinates of the input reads and generates alignments in the SAM format given single-end reads, aligns reads to reference sequence(s). All of these analyses will be shown with Krona program, which allows to show hierarchical data with pie charts.</span></p><p>Address of the bookmark: <a href="https://readthedocs.org/projects/bipype/" rel="nofollow">https://readthedocs.org/projects/bipype/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/43732/spades-tutorial-pdf</guid>
	<pubDate>Tue, 01 Feb 2022 04:56:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/43732/spades-tutorial-pdf</link>
	<title><![CDATA[Spades tutorial PDF]]></title>
	<description><![CDATA[<p>SPAdes&mdash;St. Petersburg genome Assembler&mdash;was originally developed for de novo assembly of genome sequencing data produced for cultivated microbial isolates and for single-cell genomic DNA sequencing. With time, the functionality of SPAdes was extended to enable assembly of IonTorrent data, as well as hybrid assembly from short and long reads (PacBio and Oxford Nanopore). In this article we present protocols for five different assembly pipelines that comprise the SPAdes package and that are used for assembly of metagenomes and transcriptomes as well as assembly of putative plasmids and biosynthetic gene clusters from whole-genome sequencing and metagenomic datasets.&nbsp;</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/43732" length="268093" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</guid>
	<pubDate>Wed, 08 May 2024 07:32:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</link>
	<title><![CDATA[ContigExtender: a new approach to improving de novo sequence assembly for viral metagenomics data]]></title>
	<description><![CDATA[<p dir="auto">ContigExtender, was developed to extend contigs, complementing de novo assembly. ContigExtender employs a novel recursive Overlap Layout Candidates (r-OLC) strategy that explores multiple extending paths to achieve longer and highly accurate contigs. ContigExtender is effective for extending contigs significantly in in silico synthesized and real metagenomics datasets.</p>
<p dir="auto">More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953547/</p>
<p dir="auto"><a href="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" target="_blank"><img src="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" alt="extension process" title="extension process" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/dengzac/contig-extender" rel="nofollow">https://github.com/dengzac/contig-extender</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44513/mike-an-ultrafast-assembly-and-alignment-free-approach-for-phylogenetic-tree-construction</guid>
	<pubDate>Mon, 08 Apr 2024 06:19:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44513/mike-an-ultrafast-assembly-and-alignment-free-approach-for-phylogenetic-tree-construction</link>
	<title><![CDATA[MIKE: an ultrafast, assembly-, and alignment-free approach for phylogenetic tree construction]]></title>
	<description><![CDATA[<p><span>MIKE (MinHash-based&nbsp;</span><em>k</em><span>-mer algorithm). This algorithm is designed for the swift calculation of the Jaccard coefficient directly from raw sequencing reads and enables the construction of phylogenetic trees based on the resultant Jaccard coefficient. Simulation results highlight the superior speed of MIKE compared to existing state-of-the-art methods. We used MIKE to reconstruct a phylogenetic tree, incorporating 238 yeast, 303&nbsp;</span><em>Zea</em><span>, 141&nbsp;</span><em>Ficus</em><span>, 67&nbsp;</span><em>Oryza</em><span>, and 43&nbsp;</span><em>Saccharum spontaneum</em><span>&nbsp;samples. MIKE demonstrated accurate performance across varying evolutionary scales, reproductive modes, and ploidy levels, proving itself as a powerful tool for phylogenetic tree construction.</span></p><p>Address of the bookmark: <a href="https://github.com/Argonum-Clever2/mike" rel="nofollow">https://github.com/Argonum-Clever2/mike</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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