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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/8159?offset=10</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37937/frodock-20-fast-protein%E2%80%93protein-docking-server</guid>
	<pubDate>Wed, 17 Oct 2018 04:31:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37937/frodock-20-fast-protein%E2%80%93protein-docking-server</link>
	<title><![CDATA[FRODOCK 2.0: fast protein–protein docking server]]></title>
	<description><![CDATA[<p><span>frodock: a&nbsp;user-friendly protein&ndash;protein docking server based on an improved version of FRODOCK that includes a complementary knowledge-based potential. The web interface provides a very effective tool to explore and select protein&ndash;protein models and interactively screen them against experimental distance constraints. The competitive success rates and efficiency achieved allow the retrieval of reliable potential protein&ndash;protein binding conformations that can be further refined with more computationally demanding strategies.</span></p><p>Address of the bookmark: <a href="http://frodock.chaconlab.org/" rel="nofollow">http://frodock.chaconlab.org/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41863/ppai-a-web-server-for-predicting-protein-aptamer-interactions</guid>
	<pubDate>Fri, 12 Jun 2020 07:26:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41863/ppai-a-web-server-for-predicting-protein-aptamer-interactions</link>
	<title><![CDATA[PPAI: a web server for predicting protein-aptamer interactions]]></title>
	<description><![CDATA[<p><span>PPAI can query aptamers and proteins, predict aptamers and predict protein-aptamer interactions in batch mode precisely and efficiently, which would be a novel bioinformatics tool for the research of protein-aptamer interactions. PPAI web-server is freely available at&nbsp;</span><a href="http://39.96.85.9/PPAI">http://39.96.85.9/PPAI</a></p><p>Address of the bookmark: <a href="http://39.96.85.9/PPAI/" rel="nofollow">http://39.96.85.9/PPAI/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4295/rcsb-pdb-sept13-release</guid>
	<pubDate>Thu, 05 Sep 2013 15:07:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4295/rcsb-pdb-sept13-release</link>
	<title><![CDATA[RCSB PDB Sept'13 Release]]></title>
	<description><![CDATA[<p>RCSB PDB Sept'13 Release offers following new features:</p><p>- New tools to search for drugs and drug targets<br />- Improved interface for 3D visualisation using Jmol/JSmol<br />- An update to the representation of protein symmetry and stoichiometry.<br />- Improvements when performing sequence searches.</p><p>Reference</p><p><a href="http://www.rcsb.org/pdb/static.do?p=general_information/whats_new.jsp?b=1308">http://www.rcsb.org/pdb/static.do?p=general_information/whats_new.jsp?b=1308</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5210/sandelin-group</guid>
  <pubDate>Mon, 30 Sep 2013 19:12:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Sandelin group]]></title>
  <description><![CDATA[
<p>Sandelin group have a deep interest in most biology, but focus on gene regulation and the many areas that are connected with this, including transcriptomics, epigenetics and technological and informatics aspects.</p>

<p>The group is both computational and experimental.</p>

<p>We ask biological questions to large datasets made using novel genomics techniques, with the help of computers. One of the strengths in the group are the many connections to high-profile experimental laboratories which supply data to be analyzed.</p>

<p>Lab webpage @ http://people.binf.ku.dk/albin/Sandelin_group_at_the_Bioinformatic_Centre/The_Sandelin_group.html</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/7214/lapti-lab</guid>
  <pubDate>Thu, 12 Dec 2013 18:19:12 -0600</pubDate>
  <link></link>
  <title><![CDATA[LAPTI Lab]]></title>
  <description><![CDATA[
<p>The main theme of our research is the understanding of how genetic information is decoded from DNA into RNA and proteins. Someone may find this topic a little strange and argue that we already know how this is happening.</p>

<p>Translational recoding. </p>

<p>RNA editing. </p>

<p>Evolution of the genetic code and translation.</p>

<p>More at http://lapti.ucc.ie/research.html</p>

<p>Lab page http://lapti.ucc.ie/index.html</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13338/protein-function-annotation-and-machine-learning-upmc-paris-france</guid>
  <pubDate>Sat, 02 Aug 2014 01:22:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Protein function annotation and machine learning - UPMC - Paris, France]]></title>
  <description><![CDATA[
<p>Protein function annotation and machine learning - UPMC - Paris, France</p>

<p>Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.</p>

<p>We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.</p>

<p>Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>Start date: September 1st, 2014<br />Contact Person: Alessandra Carbone<br />Contact: alessandra.carbone@lip6.fr</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18820/jrfsrf-at-university-of-calcutta</guid>
  <pubDate>Fri, 31 Oct 2014 08:53:10 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF/SRF at University of Calcutta]]></title>
  <description><![CDATA[
<p>Applications are invited to appear at a walk-in-interview for one post of Junior Research Fellow in the DBT(DBT Twinning NER) sponsored project entitled “Protein folding kinetics is a selection force on shaping codon usage bias in the high expression genes” in the room of the HOD, Department of Biotechnology and the Coordinator, DR. B. C. Guha Centre for Genetic Engineering and Biotechnology, University College of Science, 35 Ballygunge Circular Road, Kolkata 700019 on the 12th November, 2014 at 3:00 p.m.</p>

<p>Essential qualifications: First class M. Sc. in any branch of life sciences and qualified CSIR-UGC NET/GATE Examination.</p>

<p>Desirable qualifications: Practical experience in biochemical and biophysical studies of proteins</p>

<p>Emoluments: as per DBT norms</p>

<p>The project is tenable for two years, initially for one year.</p>

<p>Age: Below 28 years (relaxable in the case of SC/ST/OBC/women candidates)</p>

<p>Candidates are requested to bring two sets of complete applications on plain paper furnishing bio-data and copies of attested certificates along with originals (for verification) on the date of interview.</p>

<p>No TA/DA is admissible for candidates appearing at the interview.</p>

<p>Dr. Rajat Banerjee<br />Assistant Professor<br />Department of Biotechnology and<br />Dr. B. C. Guha Centre for Genetic Engineering and Biotechnology<br />University College of Science<br />35, Ballygunge Circular Road<br />Kolkata 700019</p>

<p>Advertisement: www.caluniv.ac.in/news/jrf_biotech_2.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</guid>
	<pubDate>Fri, 03 Mar 2017 05:15:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31278/metapred2cs</link>
	<title><![CDATA[MetaPred2CS]]></title>
	<description><![CDATA[<p style="text-align: justify;"><strong>MetaPred2CS Web server&nbsp;</strong>is a meta-predictor based on&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/17160063">Support Vector Machine (SVM)</a>&nbsp;that combines 6 individual sequence based protein-protein interaction prediction methods to predict&nbsp;<strong>prokaryotic two-component system&nbsp;</strong>protein-protein interactions (PPIs). The methods implemented in MetaPred2CS are 2 co-evolutionary methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11933068">in-silico two hybrid (i2h)</a>&nbsp;and&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/11707606">mirror tree (MT)</a>&nbsp;methods and 4 genomics context based methods:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/15947018">phylogenetic profiling (PP)</a>,&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/10573422">gene fusion (GF)</a>,&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene neighbourhood (GN)</a>&nbsp;and and&nbsp;<a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0030043">gene operon methods (GO)</a>.</p>
<p>&nbsp;http://metapred2cs.ibers.aber.ac.uk/</p><p>Address of the bookmark: <a href="https://github.com/martinjvickers/MetaPred2CS" rel="nofollow">https://github.com/martinjvickers/MetaPred2CS</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34744/foldit-solve-puzzles-for-science</guid>
	<pubDate>Thu, 21 Dec 2017 15:17:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34744/foldit-solve-puzzles-for-science</link>
	<title><![CDATA[Foldit: Solve Puzzles for Science]]></title>
	<description><![CDATA[<p><span>Foldit</span><span>&nbsp;is an online puzzle video game about protein&nbsp;</span><span>folding. It</span><span>&nbsp;is part of an experimental research project developed by the University of Washington, Center for Game Science, in collaboration with the UW Department of Biochemistry. The objective of&nbsp;</span><span>Foldit</span><span>&nbsp;is to&nbsp;</span><span>fold</span><span>&nbsp;the structures of selected proteins as perfectly as possible</span></p>
<p>https://fold.it/portal/</p><p>Address of the bookmark: <a href="https://fold.it/" rel="nofollow">https://fold.it/</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44882/fantasia</guid>
	<pubDate>Wed, 20 Aug 2025 02:48:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44882/fantasia</link>
	<title><![CDATA[FANTASIA]]></title>
	<description><![CDATA[<p dir="auto">FANTASIA is an advanced pipeline for the automatic functional annotation of protein sequences using state-of-the-art protein language models. It integrates deep learning embeddings and in-memory similarity searches, retrieving reference vectors from a PostgreSQL database with pgvector, to associate Gene Ontology (GO) terms with proteins.</p>
<p>https://www.nature.com/articles/s42003-025-08651-2</p><p>Address of the bookmark: <a href="https://github.com/CBBIO/FANTASIA" rel="nofollow">https://github.com/CBBIO/FANTASIA</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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