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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32379?offset=310</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44783/when-chromosomes-shift-understanding-chromosome-rearrangement-and-human-disease</guid>
	<pubDate>Fri, 11 Apr 2025 01:07:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44783/when-chromosomes-shift-understanding-chromosome-rearrangement-and-human-disease</link>
	<title><![CDATA[When Chromosomes Shift: Understanding Chromosome Rearrangement and Human Disease]]></title>
	<description><![CDATA[<p>In the vast and complex world of genetics, our chromosomes are like carefully arranged bookshelves &mdash; each holding critical information that defines who we are. But what happens when those books are shuffled, inverted, or swapped? The answer lies in a phenomenon known as <strong>chromosome rearrangement</strong>, a powerful force behind many human diseases, from developmental disorders to cancer.</p><h2>What Are Chromosome Rearrangements?</h2><p><strong>Chromosome rearrangements</strong> are structural changes that alter the normal configuration of chromosomes. These changes can involve large segments of DNA &mdash; from thousands to millions of base pairs &mdash; and can occur <strong>spontaneously</strong>, be <strong>inherited</strong>, or result from <strong>exposure to mutagens</strong> (like radiation or chemicals).</p><h3>Common Types of Rearrangements:</h3><ol>
<li>
<p><strong>Deletions</strong> &ndash; Loss of a chromosome segment</p>
</li>
<li>
<p><strong>Duplications</strong> &ndash; Repetition of a segment</p>
</li>
<li>
<p><strong>Inversions</strong> &ndash; A segment breaks off, flips, and reattaches</p>
</li>
<li>
<p><strong>Translocations</strong> &ndash; Segments exchange places between non-homologous chromosomes</p>
</li>
<li>
<p><strong>Insertions</strong> &ndash; A segment is inserted into another part of the genome</p>
</li>
</ol><p>These changes can disrupt genes directly or affect gene regulation, leading to disease.</p><h2>How Do Chromosome Rearrangements Cause Disease?</h2><p>The impact of a rearrangement depends on <strong>which genes are involved</strong>, <strong>how much DNA is affected</strong>, and <strong>when the rearrangement occurs</strong> (in development vs. adulthood). Here are some key mechanisms:</p><ul>
<li>
<p><strong>Gene disruption</strong>: Breaking a gene can lead to loss of function or the creation of a non-functional protein.</p>
</li>
<li>
<p><strong>Gene fusion</strong>: Joining parts of two genes may form a novel hybrid gene with new functions (common in cancer).</p>
</li>
<li>
<p><strong>Dosage effects</strong>: Extra or missing gene copies can disturb the balance of gene expression.</p>
</li>
<li>
<p><strong>Position effects</strong>: Moving a gene to a new regulatory environment may silence or over-activate it.</p>
</li>
</ul><h2>Chromosome Rearrangements in Human Disease</h2><h3>1. <strong>Developmental Disorders</strong></h3><ul>
<li>
<p><strong>Cri-du-chat syndrome</strong>: Caused by a deletion on chromosome 5p. Affected infants often have a high-pitched cry and intellectual disability.</p>
</li>
<li>
<p><strong>Williams syndrome</strong>: Results from a microdeletion on chromosome 7q, affecting genes related to cardiovascular and cognitive function.</p>
</li>
</ul><h3>2. <strong>Cancer</strong></h3><p>Cancer is perhaps the most striking example of disease caused by chromosome rearrangements.</p><ul>
<li>
<p><strong>Chronic Myeloid Leukemia (CML)</strong>: Caused by a translocation between chromosomes 9 and 22, forming the <em>Philadelphia chromosome</em>. This creates the <strong>BCR-ABL fusion gene</strong>, which drives uncontrolled cell growth.</p>
</li>
<li>
<p><strong>Burkitt lymphoma</strong>: Involves translocation of the <strong>MYC</strong> gene, leading to excessive cell division.</p>
</li>
<li>
<p><strong>Ewing sarcoma</strong>: A fusion of EWSR1 and FLI1 genes through translocation promotes tumor development.</p>
</li>
</ul><h3>3. <strong>Infertility and Miscarriages</strong></h3><p>Balanced rearrangements (like inversions or translocations) in carriers may not cause disease directly but can result in:</p><ul>
<li>
<p><strong>Recurrent miscarriages</strong></p>
</li>
<li>
<p><strong>Infertility</strong></p>
</li>
<li>
<p><strong>Birth defects in offspring</strong></p>
</li>
</ul><h2>Detecting Rearrangements</h2><p>Thanks to modern genomics, chromosome rearrangements can now be detected with high precision using:</p><ul>
<li>
<p><strong>Karyotyping</strong> &ndash; Classic method for detecting large rearrangements</p>
</li>
<li>
<p><strong>FISH (Fluorescence In Situ Hybridization)</strong> &ndash; Uses fluorescent probes to target specific DNA sequences</p>
</li>
<li>
<p><strong>Array CGH (Comparative Genomic Hybridization)</strong> &ndash; Detects copy number changes across the genome</p>
</li>
<li>
<p><strong>Whole Genome Sequencing (WGS)</strong> &ndash; Identifies even small or complex rearrangements at base-pair resolution</p>
</li>
</ul><h2>Looking Forward: The Future of Chromosome Medicine</h2><p>Understanding chromosome rearrangements is now central to:</p><ul>
<li>
<p><strong>Personalized medicine</strong></p>
</li>
<li>
<p><strong>Genetic counseling</strong></p>
</li>
<li>
<p><strong>Targeted therapies</strong>, especially in cancer (e.g., tyrosine kinase inhibitors for BCR-ABL fusion)</p>
</li>
</ul><p>With the rise of long-read sequencing and single-cell genomics, even previously &ldquo;invisible&rdquo; rearrangements are being uncovered, offering new insights into both rare diseases and common conditions.</p><h2>Final Thoughts</h2><p>Chromosome rearrangements remind us that genetics isn't just about which genes we have &mdash; but where they are, how they're arranged, and when they're active. As our tools grow sharper, so does our ability to diagnose, understand, and treat diseases rooted in genomic architecture.</p><p>In a way, the genome is like a book not just defined by its words, but also by how the chapters are ordered. Rearranging them can create a new story &mdash; sometimes harmful, sometimes insightful &mdash; and understanding these changes is key to writing a healthier future.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5310/bergman-lab</guid>
  <pubDate>Thu, 03 Oct 2013 17:20:09 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bergman Lab]]></title>
  <description><![CDATA[
<p>Broad area of research:</p>

<p>Genome Annotation and Functional Genomics</p>

<p>Bergman Lab is actively engaged in the development and application of computational methods to improve the annotation of functional biological features in genome sequences.  Bergman Lab work focuses on improving annotation of non-protein-coding regions of the genome including conserved noncoding sequences (CNSs), cis-regulatory modules (CRMs), transcription factor binding sites (TFBSs), transposable elements (TEs) and noncoding RNA (ncRNA) genes. Current projects include improving the (i) annotation of TEs in the fly and yeast genomes, (ii) annotation of CRMs and TFBSs in the fly genome, and (iii) analysis of transposon knockout collections in flies. Research in this area is supported by the EC FP7 programme.</p>

<p>Genome and Molecular Evolution<br />Text and Data Mining</p>

<p>More @ http://bergmanlab.smith.man.ac.uk/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2488/tivicay%C2%AE-dolutegravir-50-mg-tablets-for-hiv-1</guid>
	<pubDate>Fri, 16 Aug 2013 09:00:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2488/tivicay%C2%AE-dolutegravir-50-mg-tablets-for-hiv-1</link>
	<title><![CDATA[Tivicay® (dolutegravir) 50-mg tablets for HIV-1]]></title>
	<description><![CDATA[<p>FDA has approved Viiv Healthcare&rsquo;s integrase inhibitor Tivicay&reg; (dolutegravir) 50-mg tablets, for use with other antiretroviral agents in treating HIV-1 infection. ViiV Healthcare is an HIV therapeutics company established in 2009 by GlaxoSmithKline and Pfizer.</p><p>Tivicay is indicated for infected adults, both treatment-naive and treatment-experienced, including those treated with other integrase strand transfer inhibitors; as well as for children aged 12 years and older weighing at least 40 kg (approx. 88 lbs). The drug - which was used without a pharmacokinetic boosting agent - interferes with one of the enzymes necessary for HIV to multiply, and can be taken with or without food and at any time of day.</p><p>http://www.fda.gov/ForConsumers/ByAudience/ForPatientAdvocates/HIVandAIDSActivities/ucm364869.htm</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</guid>
	<pubDate>Thu, 10 Oct 2013 11:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5436/the-anatomy-of-successful-computational-biology-software</link>
	<title><![CDATA[The anatomy of successful computational biology software]]></title>
	<description><![CDATA[<p>Creators of software widely used in computational biology discuss the factors that contributed to their success</p><p><em>Nature Biotechnology</em><span>&nbsp;spoke with Altschul and several other originators of computational biology software programs widely used today (</span><a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html#t1">Table 1</a><span>). The conversations explored what makes certain software tools successful, the unique challenges of developing them for biological research and how the field of computational biology, as a whole, can move research agendas forward. What follows is an edited compilation of interviews.</span></p><p>Detail @&nbsp;<a href="http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html">http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html</a></p><p>News Source @ Nature</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5663/network-analysis-indian-statistical-institute</guid>
  <pubDate>Wed, 16 Oct 2013 08:06:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Network Analysis @ Indian Statistical Institute]]></title>
  <description><![CDATA[
<p>Indian Statistical Institute Kolkata invites applications for the following posts</p>

<p>2013 Oct Advertisement from Indian Statistical Institute</p>

<p>Post: Network Analysis</p>

<p>No. of Positions:  01</p>

<p>Educational Qualifications:</p>

<p>Candidate should have passed BE/B.Tech Or Equivalent in Computer Science / Electrical Engineering / Electronics / Information Technology / Bioinformatics / Biotechnology with throughout first Class<br />Experience:</p>

<p>(details of experience required)<br />Pay Scale: INR Rs.16000-20000/-P.M.</p>

<p>Walk-In-Interview : 22 Oct 2013 at 10:30 AM</p>

<p>Download Official Notification:<br />http://www.isical.ac.in/JobApplicationFiles/MIU_0310201311433700.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38659/detail-annotation-of-genes</guid>
	<pubDate>Fri, 11 Jan 2019 05:23:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38659/detail-annotation-of-genes</link>
	<title><![CDATA[Detail annotation of genes !]]></title>
	<description><![CDATA[<p>gene_info recalculated daily<br>---------------------------------------------------------------------------<br> tab-delimited<br> one line per GeneID<br> Column header line is the first line in the file.<br> Note: subsets of gene_info are available in the DATA/GENE_INFO<br> directory (described later)<br>---------------------------------------------------------------------------</p>
<p>tax_id:<br> the unique identifier provided by NCBI Taxonomy<br> for the species or strain/isolate</p>
<p>GeneID:<br> the unique identifier for a gene<br> ASN1: geneid</p>
<p>Symbol:<br> the default symbol for the gene<br> ASN1: gene-&gt;locus</p>
<p>LocusTag:<br> the LocusTag value<br> ASN1: gene-&gt;locus-tag</p>
<p>Synonyms:<br> bar-delimited set of unofficial symbols for the gene</p>
<p>dbXrefs:<br> bar-delimited set of identifiers in other databases<br> for this gene. The unit of the set is database:value.<br> Note that HGNC and MGI include 'HGNC' and 'MGI', respectively,<br> in the value part of their identifier. Consequently,<br> dbXrefs for these databases will appear like:<br> HGNC:HGNC:1100<br> This would be interpreted as database='HGNC', value='HGNC:1100'<br> Example for MGI:<br> MGI:MGI:104537<br> This would be interpreted as database='MGI', value='MGI:104537'</p>
<p>chromosome:<br> the chromosome on which this gene is placed.<br> for mitochondrial genomes, the value 'MT' is used.</p>
<p>map location:<br> the map location for this gene</p>
<p>description:<br> a descriptive name for this gene</p>
<p>type of gene:<br> the type assigned to the gene according to the list of options<br> provided in https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/lxr/source/src/objects/entrezgene/entrezgene.asn</p>
<p><br>Symbol from nomenclature authority:<br> when not '-', indicates that this symbol is from a<br> a nomenclature authority</p>
<p>Full name from nomenclature authority:<br> when not '-', indicates that this full name is from a<br> a nomenclature authority</p>
<p>Nomenclature status:<br> when not '-', indicates the status of the name from the <br> nomenclature authority (O for official, I for interim)</p>
<p>Other designations:<br> pipe-delimited set of some alternate descriptions that<br> have been assigned to a GeneID<br> '-' indicates none is being reported.</p>
<p>Modification date:<br> the last date a gene record was updated, in YYYYMMDD format</p>
<p>Feature type:<br> pipe-delimited set of annotated features and their classes or <br> controlled vocabularies, displayed as feature_type:feature_class <br> or feature_type:controlled_vocabulary, when appropriate; derived <br> from select feature annotations on RefSeq(s) associated with the <br> GeneID</p><p>Address of the bookmark: <a href="ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/" rel="nofollow">ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5748/troyanskaya-lab</guid>
  <pubDate>Fri, 18 Oct 2013 10:57:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Troyanskaya  Lab]]></title>
  <description><![CDATA[
<p>In our research, we combine computational methods with an experimental component in a unified effort to develop comprehensive descriptions of genetic systems of cellular controls, including those whose malfunctioning becomes the basis of genetic disorders, such as cancer, and others whose failure might produce developmental defects in model systems.</p>

<p>Research Interest<br />Genomic Data Integration</p>

<p>Microarray Analysis</p>

<p>Gene and Protein Function Prediction</p>

<p>Detection and Analysis of Chromosomal Abnormalities and Functional Evolution</p>

<p>Integration of Computation and Experiments</p>

<p>Identification of Biological Networks and Pathways</p>

<p>Evaluation and Validation of Computational Predictions</p>

<p>Scalable Visualization-Based Data Analysis</p>

<p>More @ http://reducio.princeton.edu/cm/<br />PI page @ http://reducio.princeton.edu/cm/ogt</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42923/flanker</guid>
	<pubDate>Sat, 27 Feb 2021 22:04:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42923/flanker</link>
	<title><![CDATA[Flanker]]></title>
	<description><![CDATA[<p><span>Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of&nbsp;<span>mobile genetic elements (</span>MGEs) without prior knowledge of their structure.&nbsp;<span>Flanker can be flexibly parameterised to finetune outputs by characterising upstream and downstream regions separately and investigating variable lengths of flanking sequence.</span></span></p>
<p><span><img src="https://github.com/wtmatlock/flanker/raw/main/docs/frontpage.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/wtmatlock/flanker" rel="nofollow">https://github.com/wtmatlock/flanker</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5957/assistant-professor-in-molecular-synthesis-for-drug-discovery-and-development-cbmr-lucknow</guid>
  <pubDate>Wed, 30 Oct 2013 06:42:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor in Molecular Synthesis for Drug Discovery and Development @ CBMR, Lucknow]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT FOR FACULTY POSITIONS AT CENTRE OF BIOMEDICAL RESEARCH (CBMR), LUCKNOW</p>

<p>Details of the Positions and Pay Structure:</p>

<p>03 Posts for Assistant Professor in Molecular Synthesis for Drug Discovery and Development</p>

<p>Essential Qualifications and Requirements:</p>

<p>1. PhD in Synthetic Organic Chemistry/Medicinal Chemistry with research publications in high quality international journals and first class grade at the preceding degree from recognised University/Institute in India or abroad with consistently good academic record.<br />2. Three Yrs of Post-doctoral experience in relevant area.<br />3. Below 35 Yrs of age at the time of application</p>

<p>Desirable Experience: Candidates having strong research background in organic synthesis, total synthesis of structurally complex and medicinally important natural products/drugs related to cancer, neurodegenerative diseases (neurotropically active molecules for Alzheimer's, Parkinson’s, dementia etc) and infectious diseases such as malaria, TB etc. will be preferred.</p>

<p>Interested candidates may apply with:</p>

<p>1. Filled up Application Form (download from CBMR Website: http://www.cbmr.res.in) along with the Cover Letter, Curriculum Vitae including academic record (Bachelor degree onwards), awards, honours, list of Publications and reprints of 5 best publications.<br />2. Proposed research plan (max 3-4 pages).<br />3. Names and address (with valid e-mail and Phone number) of at least 3 academic referees.<br />4. Online Payment Receipt with transaction reference no. of Rs. 1000/- (USD 100 or equivalent foreign currency) on following details.<br />Account Number: 30054847814 Name: Director, Centre of Biomedical Research<br />Bank: STATE BANK OF INDIA, SGPGI Campus Branch, LUCKNOW</p>

<p>IFSC Code: SBIN0007789<br />MICR No: 22602034</p>

<p>Applications can be sent by registered/speed post or by e-mail to the following address:</p>

<p>The Director,<br />Centre of Biomedical Research (CBMR),<br />Sanjay Gandhi PGI Campus,<br />Raebareli Road, Lucknow-226014<br />e-mail: cbmr.admin@cbmr.res.in,<br />gp.pandey@cbmr.res.in</p>

<p>More Info:</p>

<p>http://www.cbmr.res.in/career/Advertisement%20for%20the%20post%20of%20Professors%20and%20Assistant%20Professors.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43683/genview-a-phylogeny-based-comparative-genomics-software-to-analyze-the-genetic-environment-of-genes</guid>
	<pubDate>Tue, 28 Dec 2021 01:49:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43683/genview-a-phylogeny-based-comparative-genomics-software-to-analyze-the-genetic-environment-of-genes</link>
	<title><![CDATA[GEnView: A phylogeny based comparative genomics software to analyze the genetic environment of genes]]></title>
	<description><![CDATA[<p><span>A phylogeny based comparative genomics software to analyze the genetic environment of genes. The user can select one or several taxa and provide one or several reference protein(s). Genomes and plasmids (based on user choice) will be downloaded from the NCBI Assembly/NR database and searched for the respective gene. Alternatively, custom genomes can be provided. User selected stretches (20kbp by default) of the genes genetic environment are extracted, annotated and aligned between all genomes. The sequences are then visualized, enabling comparison of synteny and gene content.</span></p>
<p><span>More at&nbsp;https://pubmed.ncbi.nlm.nih.gov/34951622/</span></p><p>Address of the bookmark: <a href="https://github.com/EbmeyerSt/GEnView" rel="nofollow">https://github.com/EbmeyerSt/GEnView</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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