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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32134?offset=40</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45303/the-tree-that-learned-to-read-genomes</guid>
	<pubDate>Fri, 11 Sep 2026 00:51:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45303/the-tree-that-learned-to-read-genomes</link>
	<title><![CDATA[The Tree That Learned to Read Genomes]]></title>
	<description><![CDATA[<p>Imagine trying to reconstruct a family tree when many family photographs are missing, some names are unclear, and different relatives remember the past differently. This is similar to the challenge scientists face when trying to understand how organisms are related. Their family records are genomes, and the family tree is a phylogenetic tree. With modern sequencing technologies, scientists now have access to thousands of genomes, but comparing them can be difficult, especially when genomes are incomplete or poorly annotated.</p><p>A recent study by Webster and Chapman introduces Buscogeny (https://github.com/Jwebster89/Buscogeny), an open-source bioinformatics pipeline designed to make this process easier. The tool uses BUSCO (Benchmarking Universal Single-Copy Orthologs), which identifies conserved genes that are expected to occur as single copies in particular groups of organisms. These genes act like evolutionary landmarks, allowing researchers to compare genomes and investigate their relationships.</p><p>Buscogeny brings several steps of phylogenomic analysis into one workflow. It identifies BUSCO genes, extracts and aligns their sequences, removes unreliable regions, combines information from multiple genes, and uses the resulting data to construct a phylogenetic tree. It also provides quality-control information, helping researchers identify genomes that may be too incomplete for reliable analysis.</p><p>The authors demonstrate the usefulness of Buscogeny with bacterial and fungal genomes, including Alternaria. This is particularly valuable because fungal genomes can vary greatly in quality and annotation. Ultimately, Buscogeny helps transform massive amounts of genomic data into an understandable evolutionary story. Each DNA sequence becomes a clue, each conserved gene becomes a landmark, and together these clues reveal a picture of how life is connected.</p><p>More at&nbsp;https://link.springer.com/article/10.1007/s10123-025-00752-6?</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</guid>
	<pubDate>Thu, 17 Feb 2022 05:37:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</link>
	<title><![CDATA[Comparative genomics visualisation tools !]]></title>
	<description><![CDATA[<p>Comparative genomics visualisation tools !</p><p>Address of the bookmark: <a href="https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative" rel="nofollow">https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43916/understanding-dump-files-from-ncbi-taxonomy-database</guid>
	<pubDate>Fri, 15 Jul 2022 04:29:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43916/understanding-dump-files-from-ncbi-taxonomy-database</link>
	<title><![CDATA[Understanding DUMP files from NCBI Taxonomy database !]]></title>
	<description><![CDATA[<p>*.dmp files are bcp-like dump from GenBank taxonomy database</p><p>General information.</p><p>Field terminator is "\t|\t"</p><p>Row terminator is "\t|\n"</p><p>&nbsp;</p><p>nodes.dmp file consists of taxonomy nodes. The description for each node includes the following</p><p>fields:</p><p>tax_id -- node id in GenBank taxonomy database</p><p>&nbsp; parent tax_id -- parent node id in GenBank taxonomy database</p><p>&nbsp; rank -- rank of this node (superkingdom, kingdom, ...)&nbsp;</p><p>&nbsp; embl code -- locus-name prefix; not unique</p><p>&nbsp; division id -- see division.dmp file</p><p>&nbsp; inherited div flag&nbsp; (1 or 0) -- 1 if node inherits division from parent</p><p>&nbsp; genetic code id -- see gencode.dmp file</p><p>&nbsp; inherited GC&nbsp; flag&nbsp; (1 or 0) -- 1 if node inherits genetic code from parent</p><p>&nbsp; mitochondrial genetic code id -- see gencode.dmp file</p><p>&nbsp; inherited MGC flag&nbsp; (1 or 0) -- 1 if node inherits mitochondrial gencode from parent</p><p>&nbsp; GenBank hidden flag (1 or 0)&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; -- 1 if name is suppressed in GenBank entry lineage</p><p>&nbsp; hidden subtree root flag (1 or 0) &nbsp; &nbsp; &nbsp; -- 1 if this subtree has no sequence data yet</p><p>&nbsp; comments -- free-text comments and citations</p><p>&nbsp;</p><p>Taxonomy names file (names.dmp):</p><p>tax_id -- the id of node associated with this name</p><p>name_txt -- name itself</p><p>unique name -- the unique variant of this name if name not unique</p><p>name class -- (synonym, common name, ...)</p><p>&nbsp;</p><p>Divisions file (division.dmp):</p><p>division id -- taxonomy database division id</p><p>division cde -- GenBank division code (three characters)</p><p>division name -- e.g. BCT, PLN, VRT, MAM, PRI...</p><p>comments</p><p>&nbsp;</p><p>Genetic codes file (gencode.dmp):</p><p>genetic code id -- GenBank genetic code id</p><p>abbreviation -- genetic code name abbreviation</p><p>name -- genetic code name</p><p>cde -- translation table for this genetic code</p><p>starts -- start codons for this genetic code</p><p>&nbsp;</p><p>Deleted nodes file (delnodes.dmp):</p><p>tax_id -- deleted node id</p><p>&nbsp;</p><p>Merged nodes file (merged.dmp):</p><p>old_tax_id&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; -- id of nodes which has been merged</p><p>new_tax_id&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; -- id of nodes which is result of merging</p><p>Citations file (citations.dmp):</p><p>cit_id -- the unique id of citation</p><p>cit_key -- citation key</p><p>pubmed_id -- unique id in PubMed database (0 if not in PubMed)</p><p>medline_id -- unique id in MedLine database (0 if not in MedLine)</p><p>url -- URL associated with citation</p><p>text -- any text (usually article name and authors).</p><p>-- The following characters are escaped in this text by a backslash:</p><p>-- newline (appear as "\n"),</p><p>-- tab character ("\t"),</p><p>-- double quotes ('\"'),</p><p>-- backslash character ("\\").</p><p>taxid_list -- list of node ids separated by a single space</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19059/ipython-interactive-notebooks</guid>
	<pubDate>Fri, 07 Nov 2014 12:07:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19059/ipython-interactive-notebooks</link>
	<title><![CDATA[IPython: Interactive notebooks]]></title>
	<description><![CDATA[<p>The IPython Notebook is a web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document.</p><p>These notebooks are normal files that can be shared with colleagues, converted to other formats such as HTML or PDF, etc. You can share any publicly available notebook by using the IPython Notebook Viewer service which will render it as a static web page. This makes it easy to give your colleagues a document they can read immediately without having to install anything.</p><p><img src="http://ipython.org/_images/9_home_fperez_prof_grants_1207-sloan-ipython_proposal_fig_ipython-notebook-specgram.png" width="985" height="916" alt="image" style="border: 0px;"><br /><br />To learn more about using the IPython Notebook, you can visit our example collection, and you can read the documentation for all the details on how to use and configure the system. The Notebook Gallery showcases many interesting notebooks covering a variety of topics, from basic programming to advanced scientific computing.</p><p>&nbsp;</p><p>More http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261</p><p>http://ipython.org/ipython-doc/1/interactive/notebook.html</p><p>Reference http://ipython.org/notebook.html</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/19838</guid>
	<pubDate>Sat, 27 Dec 2014 13:30:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/view/19838</link>
	<title><![CDATA[Interview with a bioinformatician series ...]]></title>
	<description><![CDATA[<p>The aim of this series to interviews some notable bioinformaticians to get their views on various aspects of bioinformatics research. Hopefully these answers will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.<br /><br />This series will be available at BOL every fortnight.<br /><br /><br /><br /></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29274/strudel</guid>
	<pubDate>Fri, 30 Sep 2016 09:47:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29274/strudel</link>
	<title><![CDATA[Strudel]]></title>
	<description><![CDATA[<p>Strudel is our graphical tool for visualizing genetic and physical maps of genomes for comparative purposes. The application aims to let the user examine their data at a variety of different levels of resolution, from entire maps to individual markers, and explore syntenic relationships between genomes. All browsing and interaction with Strudel happens in real-time &ndash; there is no need to wait while the maps are generated. It is built using Java 1.6 and ships with its own JRE, so there is no need for users to install or update Java.</p><p>Address of the bookmark: <a href="https://ics.hutton.ac.uk/strudel/" rel="nofollow">https://ics.hutton.ac.uk/strudel/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42326/edanchin-lab</guid>
  <pubDate>Thu, 19 Nov 2020 08:00:07 -0600</pubDate>
  <link></link>
  <title><![CDATA[Edanchin Lab]]></title>
  <description><![CDATA[
<p>My main topics of interest are:</p>

<p>The impact of non tree-like evolution such as horizontal gene transfers and hybridization on species biology<br />Evolution and adaptation of animals in the absence of sexual reproduction and the underlying mechanisms<br />Genomic signatures of adaptation to a parasitic life-style</p>

<p>More at https://edanchin.org/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43272/bioinformatics-head-bioinformatics-manager-iii-cancer-genomics-research-laboratory-at-frederick-national-laboratory</guid>
  <pubDate>Wed, 18 Aug 2021 00:19:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Head (Bioinformatics Manager III), Cancer Genomics Research Laboratory at  Frederick National Laboratory]]></title>
  <description><![CDATA[
<p>Frederick National Laboratory seeking an enthusiastic, creative, and seasoned bioinformatics professional to join our leadership team and direct the exceptional Bioinformatics Group at the Cancer Genomics Research Laboratory (CGR).  CGR has a diverse team of bioinformatics and computational scientists that support all areas of bioinformatics and data analysis (infrastructure, data QC, pipeline development and maintenance, data curation and sharing, methodology development, statistical analyses, machine learning approaches, and scientific interpretation).</p>

<p>More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&amp;c=leidosbiomed&amp;id=2040</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5209/anders-krogh-lab</guid>
  <pubDate>Mon, 30 Sep 2013 19:07:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Anders Krogh Lab]]></title>
  <description><![CDATA[
<p>In a lot of my work in bioinformatics, I have been using hidden Markov models (HMMs). As a postdoc with David Haussler at UCSC we developed the so-called profile HMMs (refs). Since then I have applied HMMs to membrane proteins (refs) and gene identification (refs) and have worked on methods for such things as discriminative estimation of HMMs (refs) and alternative decoding algorithms etc. (refs).</p>

<p>Now my main interests are in gene regulation, where we work on promoter analysis; non-coding RNA, where miRNAs and structure prediction are the main areas; and protein structure, where the group is working on methods for structure prediction from sequence. To read more about these topics, please see the research pages. </p>

<p>Lab page @ http://wiki.binf.ku.dk/User:Krogh</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43943/bioinformatics-tutorial</guid>
	<pubDate>Mon, 22 Aug 2022 23:56:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43943/bioinformatics-tutorial</link>
	<title><![CDATA[Bioinformatics Tutorial !]]></title>
	<description><![CDATA[<p>This site aims to be a useful resource for bioinformatics beginners. Feel free to jump right in with the section most relevant to you, and if you're not sure, then the place to start is definitely Unix <p>Address of the bookmark: <a href="https://astrobiomike.github.io/" rel="nofollow">https://astrobiomike.github.io/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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