<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/10659?offset=720</link>
	<atom:link href="https://bioinformaticsonline.com/related/10659?offset=720" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</guid>
	<pubDate>Wed, 21 Feb 2024 06:19:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</link>
	<title><![CDATA[pipesnake: bioinformatics best-practice analysis pipeline for phylogenomic reconstruction]]></title>
	<description><![CDATA[<p dir="auto"><span>ausarg/pipesnake</span>&nbsp;is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.</p>
<p dir="auto">The pipeline is built using&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The&nbsp;<a href="https://www.nextflow.io/docs/latest/dsl2.html">Nextflow DSL2</a>&nbsp;implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.</p><p>Address of the bookmark: <a href="https://github.com/AusARG/pipesnake" rel="nofollow">https://github.com/AusARG/pipesnake</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44930/bioinformatics-the-bridge-between-curiosity-and-discovery</guid>
	<pubDate>Mon, 24 Nov 2025 05:16:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44930/bioinformatics-the-bridge-between-curiosity-and-discovery</link>
	<title><![CDATA[Bioinformatics: The Bridge Between Curiosity and Discovery]]></title>
	<description><![CDATA[<p>In the sprawling universe of modern science, bioinformatics stands as one of the most transformative and empowering fields of our time. It is where biology meets computation, where data becomes meaning, and where curiosity becomes discovery. If you&rsquo;ve stepped into this world&mdash;or are considering it&mdash;here&rsquo;s your reminder: you&rsquo;re part of a revolution.</p><p><strong>Why Bioinformatics Matters More Than Ever</strong></p><p>Every day, our world generates massive amounts of biological data&mdash;from genome sequences to microbiome profiles to real-time pathogen surveillance. Hidden within these datasets are the answers to some of the greatest challenges humanity faces: emerging diseases, antimicrobial resistance, environmental stress, genetic disorders, sustainable agriculture, and more.</p><p>Bioinformatics isn&rsquo;t just a skill.<br />It&rsquo;s the language of the future of biology.</p><p>By mastering it, you give yourself the power to:</p><p>Decode genomes and understand life at its most fundamental level</p><p>Identify patterns no microscope could ever reveal</p><p>Predict disease outbreaks before they occur</p><p>Accelerate drug discovery with computational precision</p><p>Contribute to open-source tools that empower scientists worldwide</p><p>You don&rsquo;t just follow science&mdash;you drive it.</p><p><strong>Every Expert Was Once a Beginner</strong></p><p>Many newcomers feel intimidated. Command-line interfaces. R scripts. Python packages. Next-generation sequencing data. Complex machine learning models.</p><p>But here&rsquo;s the truth: every bioinformatician started exactly where you are now&mdash;curious, unsure, but excited.</p><p>No one writes perfect code on day one.</p><p>No one understands genomics pipelines immediately.</p><p>What makes you a bioinformatician is not perfection, but perseverance.</p><p>When your script throws a cryptic error&hellip;<br />When your data refuses to format&hellip;<br />When your pipeline runs for 6 hours only to crash&hellip;</p><p>Remember: this is part of the journey.<br />Every error teaches you. Every retry strengthens you. Every breakthrough energizes you.</p><p>Bioinformatics Is Not Just a Career&mdash;It&rsquo;s a Mindset</p><p>It&rsquo;s the mindset of:</p><p>Problem-solving.</p><p>Continuous learning.</p><p>Turning chaos into clarity.</p><p>Seeing what others can&rsquo;t.</p><p>Bioinformaticians are detectives of biological complexity. You sit at the intersection of innovation, using tools that can shape public health, medicine, agriculture, and ecology. Few fields give you such direct impact on the world.</p><p><strong>Your Contribution Matters</strong></p><p>As you work on your script, pipeline, genome, or model, remember:</p><p>Somewhere, your analysis might contribute to:</p><p>A new therapy</p><p>A faster diagnostic test</p><p>A better understanding of a pathogen</p><p>A more resilient crop</p><p>An open-source dataset that helps thousands</p><p>A discovery that rewrites textbooks</p><p>Your code may be small, but its ripple effect is powerful.</p><p>The Future Is Bioinformatics&mdash;And You Are Part of It</p><p>The world is shifting. Wet labs are integrating AI. Hospitals rely on genomic insights. Farmers use gene-level predictions. Governments monitor disease in real time. Students launch pipelines that become global tools.</p><p>This is a golden era&mdash;and you are not late.<br />You are exactly where you need to be.</p><p>Keep Pushing. Keep Learning. Keep Discovering.</p><p>Bioinformatics is a journey filled with challenges, but also with unmatched rewards.</p><p>So the next time you feel stuck, frustrated, or overwhelmed, remember:<br />You&rsquo;re building the science of tomorrow.</p><p>Be proud. Stay curious. Keep going.<br />Your work matters more than you think.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4107/natasa-przulj-lab</guid>
  <pubDate>Fri, 30 Aug 2013 06:29:17 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nataša Pržulj Lab]]></title>
  <description><![CDATA[
<p>Nataša Pržulj Lab's research involves applications of graph theory, mathematical modeling, and computational techniques to solving large-scale problems in computational and systems biology.They are interested in computational and theoretical solutions to practical problems in many areas of systems biology, planar cell polarity, proteomics, cancer informatics, and drug discovery and design.</p>

<p>More at http://www.doc.ic.ac.uk/~natasha/index.html</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24984/ra-bioinformatics-at-nii</guid>
  <pubDate>Thu, 22 Oct 2015 01:56:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at NII]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF IMMUNOLOGY</p>

<p>NEW DELHI-110067</p>

<p>Applications are invited for the position of Research Associate (RA) for the following time-bound sponsored project as per the details given below:</p>

<p>1. BTIS project entitled, “National Infrastructural Facility in the Area of Immunology” funded by DBT</p>

<p>Research Associate (One Position only)</p>

<p>Dr. Debasisa Mohanty Staff Scientist-VI deb@nii.res.in</p>

<p>Educational Qualifications: Ph.D in Bioinformatics or Biological Sciences or Biotechnology with research experience and publication record in indexed peer reviewed journals in the area of bioinformatics or computational biology.</p>

<p>Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications &amp; experience Research Associate: Rs. 36,000/- per month plus 30% HRA</p>

<p>Job description &amp; Desired Knowledge: The candidate should be well versed in Programming in PERL/C++, HTML, CGI, web sever and portal development, computational analysis of protein structure &amp; function, molecular dynamics simulations and use of high performance computing systems.</p>

<p>General Terms &amp; Conditions:-</p>

<p>1. The candidates selected for the above posts will be on contract for one year or duration of the project whichever is shorter, at a time.</p>

<p>2. No hostel/ housing facility will be provided.</p>

<p>3. Applicants may clearly mention the category they belong to i.e. SC/ST/OBC/PH and attach documentary proof of the same.</p>

<p>4. No TA/DA will be paid for attending the interview, if called for.</p>

<p>5. Apart from sending application in the prescribed format given below, candidates should send complete Curriculum Vitae along with the names of three referees. Curriculum Vitae should contain details of the experimental expertise and list of publications. 6. Canvassing in any form will be a disqualification.</p>

<p>HOW TO APPLY Interested candidates may apply directly, STRICTLY IN THE PRESCRIBED FORMAT GIVEN BELOW, through e-mail, to the Investigator of the project, clearly indicating the name of the project along with their complete C.V., Email ID, fax numbers, telephone numbers. Only Short listed candidates will be called for interview and they required to submit attested copies of all their certificates and a Demand Draft of Rs 100/- drawn on Canara Bank or Indian Bank payable at Delhi/New Delhi in favour of the Director, NII (SC/ST/PH and Women candidates are exempted from payment of fees) subject to submission of documentary proof), at the time of interview. (E-MAIL APPLICATIONS SHOULD MENTION BTIS-RA 2015 IN THE SUBJECT LINE)</p>

<p>LAST DATE OF RECEIPT OF APPLICATIONS: 29th October, 2015</p>

<p>Advertisement:</p>

<p>www1.nii.res.in/sites/default/files/projectappointments-Dr.Mohanty-29oct2015.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/6896/dna-tale-of-3-to-4-years-old-serbia-boy</guid>
	<pubDate>Tue, 26 Nov 2013 17:34:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/6896/dna-tale-of-3-to-4-years-old-serbia-boy</link>
	<title><![CDATA[DNA tale of 3 to 4 years old Serbia boy]]></title>
	<description><![CDATA[<p><span>The genome of a young boy found underground at Mal&rsquo;ta near Lake Baikal of eastern Siberia around 24,000 years ago came out as close relative of Europeans and Native Indians.</span></p><p><span>Link:</span></p><p><span><a href="http://www.nytimes.com/2013/11/21/science/two-surprises-in-dna-of-boy-found-buried-in-siberia.html?_r=0">http://www.nytimes.com/2013/11/21/science/two-surprises-in-dna-of-boy-found-buried-in-siberia.html?_r=0</a></span></p><p>&nbsp;</p><p><a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12736.html">http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12736.html</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/6232/the-cat-evolution-domestication-and-genome-10k</guid>
	<pubDate>Sun, 10 Nov 2013 14:33:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/6232/the-cat-evolution-domestication-and-genome-10k</link>
	<title><![CDATA[The Cat: evolution, domestication and Genome 10k]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/wS-3_flpX9s" frameborder="0" allowfullscreen></iframe>A public lecture by Dr Stephen J O'Brien at the UCD Earth Institute, University College Dublin, Ireland.
 
Dr O'Brien is a world leading molecular biologist and dedicated conservationist who uses the tools of molecular biology to help protect endangered species and understand devastating diseases such as cancer and AIDS. He received his PhD in Genetics from Cornell University, USA, in 1971. He then joined the prestigious National Cancer Institute, National Institutes of Health as a post-doc in 1971 and, there, served as Founder and Chief of the Laboratory of Genomic Diversity from 1986-2011.
 
In December 2011, he joined the Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, Russia, as Chief Scientific Officer. Convinced of the utility of exploring diverse species to advance our understanding of the human genome, Dr O'Brien and his team have assembled over 62,000 animal and 424,000 human tissue/DNA specimens, facilitating wide-ranging studies of disease gene associations, species adaptation and natural history. His research interests and expertise span human and comparative genomics, genetic epidemiology, HIV/AIDS, retro-virology, bioinformatics biodiversity and species conservation. Dr O'Brien is best known for documenting the remarkable genetic uniformity of African cheetahs, resolving the mammalian tree of life, describing heretofore unrecognized species of Orangutans, African forest elephants, and Bornean clouded leopards. He is credited with the discovery of CCR5 delta 32, the first of 20 human AIDS restriction genes, which imparts natural immunity to HIV. He is the one of the founders of the Genome 10K initiative, has published over 750 leading research papers, written multiple books and is adjunct professor in over 12 international leading universities.
 
The UCD Earth Institute, University College Dublin, is a multidisciplinary research and education centre with a focus on creating and sharing new knowledge. We aim to contribute to sustainable solutions for many of the pressing Earth-related problems affecting societies now and in the near future.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</guid>
	<pubDate>Sun, 06 Aug 2017 06:58:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</link>
	<title><![CDATA[Sequence - Evolution - Function; Computational Approaches in Comparative Genomics]]></title>
	<description><![CDATA[<p><em>Sequence - Evolution - Function</em><span>&nbsp;is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/books/NBK20260/" rel="nofollow">https://www.ncbi.nlm.nih.gov/books/NBK20260/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42903/katherine-belov-lab</guid>
  <pubDate>Sun, 21 Feb 2021 22:59:35 -0600</pubDate>
  <link></link>
  <title><![CDATA[Katherine Belov Lab]]></title>
  <description><![CDATA[
<p>Evolution of the adaptive immune system Marsupial and monotreme immune genes MHC Diversity and Conservation Marsupial and monotreme genomics Comparative Genomics Genetics of Tasmanian Devil facial tumour disease</p>

<p>More at https://www.sydney.edu.au/science/about/our-people/academic-staff/kathy-belov.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44614/online-resources-on-must-read-papers-in-evolutionary-biology</guid>
	<pubDate>Fri, 26 Jul 2024 01:39:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44614/online-resources-on-must-read-papers-in-evolutionary-biology</link>
	<title><![CDATA[Online resources on must-read papers in evolutionary biology]]></title>
	<description><![CDATA[<pre>Online resources on must-read papers in evolutionary biology, for a literature club.<br /><br />Below is a summary of all answers that we received.

All the best,

Jana and Xiaoyan

1.       *Nick Barton:*

- The textbook "Evolution" by Nick Barton, with resources for
  exploring the literature: Barton, N. H., Briggs, D. E. G., Eisen, J.
  A., Goldstein, D. B., &amp; Patel, N. H. (2007). Evolution. Cold Spring
  Harbor Laboratory Press.

- Papers from a course named "Classics in Evolutionary Biology":

Evolutionary Synthesis
1. Haldane, J. B. S. 1932. The causes of evolution. Longmans. New York.
   (esp. Ch. IV).
2. Fisher, R. A. 1930. The genetical theory of natural selection. Oxford
   University Press, Oxford. Selected Sections - Fundamental Theorem.

Genetic Variation
1a. Lewontin, R. C., and J. L. Hubby. 1966. A molecular approach to
the study of genic heterozygosity in natural populations. II. Amount
of variation and degree of heterozygosity in natural populations of
Drosophila pseudoobscura. Genetics. 54:595-609.

1b. Sachidandam et al. 2001. A map of human genome sequence variation
containing 1.42 million single nucleotide polymorphisms. 409: 928-33.

2. Wright S., Dobzhansky T., Hovanitz W. 1942 Genetics of natural
populations VII The allelism of lethals in the third chromosome of
Drosophila pseudoobscura. Genetics 27: 363-394.

Recombination and evolution
1. Hill, W. G., and A. Robertson. 1966. The effect of linkage on limits
to artificial selection. Genet. Res. 8:269-294.

2. Maynard Smith and Haigh. 1974. The hitch-hiking effect of a favourable
gene. Genet. Res. 23: 23-35.

Understanding sequence variation
1. Begun D. J., Aquadro C. F., 1992 Levels of naturally occurring DNA
polymorphism correlate with recombination rate in Drosophila melanogaster.
Nature 356: 519-520.

2. Green R. E., Reich D., P&auml;&auml;bo S., 2010 A draft sequence of the
Neandertal genome. Science 328: 710-722.

Quantitative Genetics:  variation in complex traits
1. Galton F., 1877 Typical laws of heredity. Nature 15: 492-495-
512-514- 532-533.

2. Turelli M., 1984 Heritable genetic variation via
mutation-selection balance: Lerch's Zeta meets the abdominal
bristle. Theor. Popul. Biol. 25: 138-193.

Quantitative Genetics:  finding the genes
1. Shrimpton A. E., Robertson A., 1988 The Isolation of polygenic factors
controlling bristle score in Drosophila melanogaster II Distribution of
third chromosome bristle effects within chromosome sections. Genetics
118: 445-459.

2. Boyle E. A., Li Y. I., Pritchard J. K., 2017 An expanded view of
complex traits: from polygenic to omnigenic. Cell 169: 1177-1186.

Neutral Evolution
1. Kimura, M. 1968. Evolutionary rate at the molecular level. Science.
217:624-626.

2a. Kern A. D., Hahn M. W., 2018 The Neutral Theory in Light of Natural
Selection. Molecular Biology and Evolution 110: 21077-6.

2b. Jensen J. D., Payseur B. A., Stephan W., Aquadro C. F., Lynch M.,
Charlesworth D., Charlesworth B., 2018 The importance of the Neutral Theory
in 1968 and 50 years on: a response to Kern and Hahn 2018. Evolution 112:
2109-4.

2c. Ellegren &amp; Galtier. 2016. Determinants of genetic diversity. Nature
Reviews Genetics.

Mutation and Genetic Variability
1. Luria, S. E., and M. Delbr&uuml;ck. 1943. Mutations of Bacteria from Virus
Sensitivity to Virus Resistance. Genetics. 28(6):491-511.

2. Hill, W G. 1982. "Rates of Change in Quantitative Traits From Fixation
of New Mutations." Proceedings of the National Academy of Sciences (U.S.A.)
79: 142-45.

Testing for selection
1. McDonald &amp; Kreitman. 1991. Adaptive protein evolution at the Adh locus
in Drosophila. Nature.

2. Begun, et al. Mol. Biol. Evol. 16, 1816-1819 (1999).

3. Siddiq et al. 2016. Experimental test and refutation of a classic case
of molecular adaptation in Drosophila melanogaster.  Nature Ecology &amp;
Evolution.

The shifting balance
1. Wright, S. 1932. The roles of mutation, inbreeding, crossbreeding and
selection in evolution. Proceedings of the VI International Congress of
Genetics: 1. pp 356-366.

2. Coyne, J.A., N.H. Barton, and M. Turelli. 1997. A critique of Wright's
shifting balance theory of evolution.  Evolution 51: 643-671.

3. Barton. 2016. Sewall Wright on Evolution in Mendelian Populations and
the "Shifting Balance". Genetics.

Evolution of Sex
1.  Muller, H.J. 1964. The relation of recombination to mutational advance.
Mutation Res. 1(1):2-9

2. McDonald et al. 2016. Sex speeds adaptation by altering the dynamics of
molecular evolution. Nature.

Kin Selection, Cooperation, and Conflict
1. Hamilton, W. D. 1964. The genetical evolution of social behaviour I.
Journal of Theoretical Biology. 7:1-52.

2. Trivers, R. L. 1974 Parent-offspring conflict. American Zoologist.
14(1):249-264.

Sexual Selection
1. Zahavi, A. 1975. Mate selection - a selection of a handicap. J. Theor.
Biol. 53:205-214.

2. Kirkpatrick, M., and Ryan, M.J. 1991. The evolution of mating
preferences and the paradox of the lek. Nature. 350:33-38.

Fitness Landscapes
1. Dean, A. 1995. A Molecular Investigation of Genotype by Environment
Interactions. Genetics. 139:19-33.

2. Costanzo et al. 2010. The Genetic Landscape of a Cell. Science.

Speciation
1. Coyne, J. A., and H. A. Orr. 1989. Patterns of speciation in Drosophila.
Evolution. 43:362-381.

2. Corbett-Detig et al. 2013. Genetic incompatibilities are widespread
within species. Nature.

2.       *Marcos Antezana:*

Valen, L. v. 1975. Energy and Evolution. University of Chicago, Department
of Biology.

3.       *Remco Folkertsma:*

1. The work by Hopi Hoekstra on local adaptation and oldfield mice

2. Poelstra, J. W., Vijay, N., Bossu, C. M., Lantz, H., Ryll, B., M&uuml;ller,
I., ... &amp; Wolf, J. B. (2014). The genomic landscape underlying phenotypic
integrity in the face of gene flow in crows. Science, 344(6190), 1410-1414.

4.       *Joshka Kaufmann and Leslie Turner*

They offer us a link to 'papers every evolutionary biologist should read',
the papers are collected by Leslie Turner.
https://static1.squarespace.com/static/53e8cb7ce4b02c4bc3aeeee4/t/5ab8fcb670a6ad55c67fcdf4/1522072758665/EvoBioClassicsRefList.pdf

5.       *Sarah Stockwell*

Matt Ridley collected classic papers in evolutionary biology and printed
part of these papers in his book Evolution (see Matt Ridley. Evolution
(Univ. of Oxford Press, 2nd edition, 2004))
</pre>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/4546/sowdhamini-lab</guid>
  <pubDate>Sun, 15 Sep 2013 09:19:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[SOWDHAMINI Lab]]></title>
  <description><![CDATA[
<p>Genome sequencing projects have enormous potential for benefiting human endeavors. However, just as acquiring a language's vocabulary does not enable one to speak it, databases that list the amino acid composition of proteins do not directly tell us much about these proteins' higher-level structure and function. The most productive way to indirectly exploit these databases has been to start with the small number of proteins that are fully-characterised and to assume that other "similar" proteins will have a related structure and function. Proteins with very similar amino acid sequence are "no-brainers", but the real test, which our group largely focuses on, is to detect the "essential" similarity in proteins whose non-critical sections have experienced random rearrangements during evolution. In such cases functionally similar proteins may have less than 25% sequence overlap.</p>

<p>More @ http://www.ncbs.res.in/sowdhamini/groups_sowdhamini.htm</p>
]]></description>
</item>

</channel>
</rss>