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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43681?offset=10</link>
	<atom:link href="https://bioinformaticsonline.com/related/43681?offset=10" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/43817/bioinfo-lab</guid>
  <pubDate>Fri, 04 Mar 2022 00:17:00 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinfo Lab]]></title>
  <description><![CDATA[
<p>The Institute of Bioinformatics conducts internationally renowned research and provides profound education in bioinformatics. Its research focuses on development and application of machine learning and statistical methods in biology and medicine.</p>

<p>Contact:<br />Computer Science Building (Science Park 3)<br />Altenberger Str. 69, A-4040 Linz, Austria<br />Tel. +43 732 2468 4520 / Fax +43 732 2468 4539<br />E-mail secretary@bioinf.jku.at</p>

<p>http://www.bioinf.jku.at/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/41496/new-machine-learning-packages-in-r</guid>
	<pubDate>Fri, 27 Mar 2020 12:11:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/41496/new-machine-learning-packages-in-r</link>
	<title><![CDATA[New Machine Learning Packages in R]]></title>
	<description><![CDATA[<h3 id="machine-learning">Machine Learning</h3><p><a href="https://cran.r-project.org/package=autokeras">autokeras</a>&nbsp;v1.0.1: Implements an interface to&nbsp;<a href="https://autokeras.com/">AutoKeras</a>, an open source software library for automated machine learning. See&nbsp;<a href="https://cran.r-project.org/web/packages/autokeras/readme/README.html">README</a>&nbsp;for an example.</p><p><a href="https://cran.r-project.org/package=MTPS">MTPS</a>&nbsp;v0.1.9: Implements functions to predict simultaneous multiple outcomes based on revised stacking algorithms as described in&nbsp;<a href="denied:doi:10.1093/bioinformatics/btz531">Xing et al. (2019)</a>. See the&nbsp;<a href="https://cran.r-project.org/web/packages/MTPS/vignettes/Guide.html">vignette</a>&nbsp;to get started.</p><p><a href="https://cran.r-project.org/package=quanteda.textmodels">quanteda.textmodels</a>&nbsp;v0.9.1: Implements methods for scaling models and classifiers based on sparse matrix objects representing textual data. It includes implementations of the&nbsp;<a href="denied:doi:10.1017/S0003055403000698">Laver et al. (2003)</a>&nbsp;wordscores model, the&nbsp;<a href="denied:arxiv:1710.08963">Perry &amp; Benoit&rsquo;s (2017)</a>&nbsp;class affinity scaling model, and the&nbsp;<a href="denied:doi:10.1111/j.1540-5907.2008.00338.x">Slapin &amp; Proksch (2008)</a>&nbsp;wordfish model. See the&nbsp;<a href="https://cran.r-project.org/web/packages/quanteda.textmodels/vignettes/textmodel_performance.html">vignette</a>&nbsp;to get started.</p><p><a href="https://cran.r-project.org/package=SeqDetect">SeqDetect</a>&nbsp;v1.0.7: Implements the automaton model found in&nbsp;<a href="https://ieeexplore.ieee.org/document/8910574">Krleža, Vrdoljak &amp; Brčić (2019)</a>&nbsp;to detect and process sequences. See the&nbsp;<a href="https://cran.r-project.org/web/packages/SeqDetect/vignettes/SequentialDetector.pdf">vignette</a>&nbsp;for examples and theory.</p><p><a href="https://cran.r-project.org/package=studyStrap">studyStrap</a>&nbsp;v1.0.0: Implements multi-Study Learning algorithms such as Merging, Study-Specific Ensembling (Trained-on-Observed-Studies Ensemble), the Study Strap, and the Covariate-Matched Study Strap. and offers over 20 similarity measures. See&nbsp;<a href="denied:doi:10.1101/856385">Kishida, et al. (2019)</a>&nbsp;for background and the&nbsp;<a href="https://cran.r-project.org/web/packages/studyStrap/vignettes/vignette.html">vignette</a>&nbsp;for how to use the package.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41107/machine-learning-in-perl</guid>
	<pubDate>Sun, 16 Feb 2020 15:32:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41107/machine-learning-in-perl</link>
	<title><![CDATA[Machine learning in Perl]]></title>
	<description><![CDATA[<p>this is a fourth blog post in the Machine learning in Perl series, focusing on the&nbsp;<a href="https://metacpan.org/pod/AI::MXNet">AI::MXNet</a>, a Perl interface to Apache MXNet, a modern and powerful machine learning library.</p>
<p>If you're interested in refreshing your memory or just new to the series, please check previous entries over here:&nbsp;<a href="http://blogs.perl.org/users/sergey_kolychev/2017/02/machine-learning-in-perl.html">1</a>&nbsp;<a href="http://blogs.perl.org/users/sergey_kolychev/2017/04/machine-learning-in-perl-part2-a-calculator-handwritten-digits-and-roboshakespeare.html">2</a>&nbsp;<a href="http://blogs.perl.org/users/sergey_kolychev/2017/10/machine-learning-in-perl-part3-deep-convolutional-generative-adversarial-network.html">3</a></p>
<p><a href="https://metacpan.org/pod/AI::MXNet">https://metacpan.org/pod/AI::MXNet</a></p><p>Address of the bookmark: <a href="http://blogs.perl.org/users/sergey_kolychev/2018/07/machine-learning-in-perl-kyuubi-goes-to-a-modelzoo-during-the-starry-night.html" rel="nofollow">http://blogs.perl.org/users/sergey_kolychev/2018/07/machine-learning-in-perl-kyuubi-goes-to-a-modelzoo-during-the-starry-night.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43877/crowdgo-machine-learning-and-semantic-similarity-guided-consensus-gene-ontology-annotation</guid>
	<pubDate>Thu, 26 May 2022 00:59:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43877/crowdgo-machine-learning-and-semantic-similarity-guided-consensus-gene-ontology-annotation</link>
	<title><![CDATA[CrowdGO: Machine learning and semantic similarity guided consensus Gene Ontology annotation]]></title>
	<description><![CDATA[<p dir="auto">CrowdGO is a protein Gene Ontology predictor using a meta approach, analyzing the predictions of other tools in order to get an improved precision and recall.</p>
<p dir="auto">Please note that the CrowdGO snakemake workflow is currently only tested on Ubuntu. It should work on OSX, but please report any errors to <a href="mailto:maarten.reijnders@unil.ch">maarten.reijnders@unil.ch</a> or create an issue.</p>
<p>https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010075</p><p>Address of the bookmark: <a href="https://gitlab.com/mreijnders/crowdgo" rel="nofollow">https://gitlab.com/mreijnders/crowdgo</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/1123/online-courses-for-biology-beginners</guid>
	<pubDate>Thu, 18 Jul 2013 13:28:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/1123/online-courses-for-biology-beginners</link>
	<title><![CDATA[Online Courses for biology beginners]]></title>
	<description><![CDATA[<p>Most of the time we face some biological problems while analysing our data computationally. This bookmark is being created to provide list of all free online courses at one place. If you know any other good online cource resources to learn biology please let me know.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://ocw.mit.edu/courses/index.htm" rel="nofollow">http://ocw.mit.edu/courses/index.htm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/8828/drew-berry-animations-of-unseeable-biology</guid>
	<pubDate>Mon, 10 Mar 2014 06:44:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/8828/drew-berry-animations-of-unseeable-biology</link>
	<title><![CDATA[Drew Berry: Animations of unseeable biology]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/WFCvkkDSfIU" frameborder="0" allowfullscreen></iframe>http://www.ted.com We have no ways to directly observe molecules and what they do -- Drew Berry wants to change that. At TEDxSydney he shows his scientifically accurate (and entertaining!) animations that help researchers see unseeable processes within our own cells.

TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes. Featured speakers have included Al Gore on climate change, Philippe Starck on design, Jill Bolte Taylor on observing her own stroke, Nicholas Negroponte on One Laptop per Child, Jane Goodall on chimpanzees, Bill Gates on malaria and mosquitoes, Pattie Maes on the "Sixth Sense" wearable tech, and "Lost" producer JJ Abrams on the allure of mystery. TED stands for Technology, Entertainment, Design, and TEDTalks cover these topics as well as science, business, development and the arts. Closed captions and translated subtitles in a variety of languages are now available on TED.com, at http://www.ted.com/translate

If you have questions or comments about this or other TED videos, please go to http://support.ted.com]]></description>
	
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9859/bioinformatics-jrfsrf-position-at-university-of-hyderabad</guid>
  <pubDate>Tue, 15 Apr 2014 20:07:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at University of Hyderabad]]></title>
  <description><![CDATA[
<p>UNIVERSITY OF HYDERABAD SCHOOL OF LIFE SCIENCES </p>

<p>Applications are invited from qualified individuals for a JRF/SRF position (sponsored by DBT/DST) at Prof. Jagan Pongubala’s laboratory, University of Hyderabad. Dr. Pongubala’s laboratory is investigating the molecular pathways that control the development of innate and adaptive immune cell types utilizing a combination of genetic, molecular and computational approaches.</p>

<p>JRF/SRF</p>

<p>Masters degree in Bioinformatics  (M.Sc./M.Tech.)</p>

<p>Rs. 12,000+HRA<br />Rs. 16,000+HRA</p>

<p>Initial appointment is for one year and  subjected to renewal up to 2 years</p>

<p>Candidates selected for the above position would have a choice to work on computational biology or experimental  biology. Candidates interested to work on computational biology are expected to perform high-throughput sequencing  (NGS) data analysis and should have a strong background in Bioinformatics &amp; Computational Biology, good  programming skills particularly Perl, Python, R and work experience in Linux environment.</p>

<p>Candidates interested to work on experimental biology should have work experience in techniques that are routinely  used in molecular biology and mammalian cell culture. A basic knowledge of bioinformatics is also desired. </p>

<p>Applicants for the above positions should have a Masters degree (M.Tech/M.Sc) with an aggregate marks greater  than 70% or a 7.5 CGPA. Candidates having JRF-fellowship through CSIR/UGC/ICMR/DBT will be encouraged  to enroll into Ph.D. program. The interested candidates having excellent organizational skills and the ability to work  in a team environment with an aspiration to learn new techniques and explore new scientific areas are requested to generate their resume using the link https://cvmkr.com/CV/new#0 and forward to pongubalajagan@gmail.com</p>

<p>Review of applications will begin immediately and continue until the position is filled. Eligible candidates will be called for an interview. No TA/ DA will be paid for attending the interview or at the time of joining the post. Applicants should note that the appointment is purely temporary and subjected to renewal up to three years and there is no Right to Claim for any regular appointment with the University.</p>

<p>Corresponding address: Jagan Pongubala, Ph.D.<br />Department of Animal Sciences<br />School of Life Sciences, Room:S44<br />University of Hyderabad<br />Gachibowli, Hyderabad 500046</p>

<p>Advertisement: https://www.uohyd.ac.in/images/recruitment/jrf-srf_130414.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10262/research-fellow-phd-candidate-in-computational-biology-%E2%80%93-2-positions</guid>
  <pubDate>Fri, 25 Apr 2014 20:19:58 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research fellow (PhD candidate) in computational biology – 2 positions]]></title>
  <description><![CDATA[
<p>At the Department of Informatics two 4-year positions as research fellow are available in the field of computational biology connected to the Computational Biology Unit. The positions are linked to the project “Integrated genomics - linking transcriptional and translational regulation over developmental time” supported by the Bergen Research Foundation</p>

<p>The fate of a cell is ultimately the product of the regulation of its genes. Gene regulation is a coordinated process acting at multiple levels of which transcription and translation are the most prominent. The Valen group is dedicated to the fundamental question of how transcription and translation is integrated to obtain the desired protein abundance. The recent development of high-throughput next generation sequencing techniques to monitor both active translation and transcription has made it possible to study this connection at the genome scale.</p>

<p>This project aims to elucidate the links between regulation of translation and transcription. The applicant will analyze next generation sequencing data and model gene regulation on a genome-wide level to identify the features that affect the translational output of transcripts. The work will be done in close collaboration with experimental scientists who will test the predictions of the computational models.</p>

<p>Additional information on the position can be obtained by contacting Eivind Valen (eivind.valen@ii.uib.no).</p>

<p>The research fellow must take part in the University’s approved PhD program leading to the degree within a time limit of 3 years. Application for admission to the PhD program, including a project plan outline for the training module, will be worked out in collaboration with the research group in question.</p>

<p>In total, the fellowship period is 4 years, 25 % of this will be allocated to teaching and/or administrative duties. The fellowship period may be reduced if the successful applicant has held previous employment as a research fellow or similar.</p>

<p>http://www.jobbnorge.no/en/available-jobs/job/102235/research-fellow-phd-candidate-in-computational-biology-2-positions</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10460/assistant-professor-at-jawaharlal-nehru-university-in-delhi</guid>
  <pubDate>Wed, 07 May 2014 00:29:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at Jawaharlal Nehru University in Delhi]]></title>
  <description><![CDATA[
<p>Advt. No. RC/48/2014</p>

<p>SCHOOL OF COMPUTATIONAL AND INTEGRATIVE SCIENCES (SC&amp;IS)</p>

<p>ESSENTIAL QUALIFICATION : - M.Sc./M.Tech. in Physics/ Chemistry/ Biology/ Mathematics/ Statistics/ Bioinformatics/ Computational Biology. Ph.D. in the broad areas of Bioinformatics/ Computational Biology. Candidates must have demonstrated capabilities in terms of high impact research publications in either of the above mentioned areas.</p>

<p>Scale of Pay : - 15600-39100/- (PB-III) AGP Rs. 6000/-</p>

<p>For more details on Centre/School, Specializations etc. please visit JNU website www.jnu.ac.in or contact Section Officer, Room Nos. 131-132, Recruitment Cell, Administrative Block, JNU, New Delhi – 110067, Email: recruitmentjnu2013@gmail.com The last date for the receipt of application is 15 May, 2014.</p>

<p>http://www.jnu.ac.in/Career/</p>

<p>http://www.jnu.ac.in/Career/ADVTNo_RC_48_2014.pdf<br />Last Apply Date:</p>

<p>15 May 2014</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10841/ra-at-iisr-kozhikode</guid>
  <pubDate>Thu, 15 May 2014 10:08:09 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA at IISR Kozhikode]]></title>
  <description><![CDATA[
<p>INDIAN INSTITUTE OF SPICES RESEARCH<br />(Indian Council of Agricultural Research)<br />Marikunnu P.O., Kozhikode – 673 012, Kerala</p>

<p>Walk- in- Test cum Interview (based on test) for the selection of Research Associate</p>

<p>under the scheme “Distributed Information Sub Centre –DISC” &amp; Research Assistant under scheme “Phytophthora, Fusarium and Ralstonia diseases of Horticultural and Field Crops” will be held at this Institute as per details indicated below.</p>

<p>WALK -IN- TEST CUM INTERVIEW</p>

<p>Name of the post : Research Associate</p>

<p>Date of Interview : 21-05-2014 at 10.00 AM</p>

<p>No. of posts : One</p>

<p>Qualifications : a)Essential</p>

<p>Ph.D Degree in Bioinformatics OR :  Masters degree in Bioinformatics with a minimum of<br />60% marks or equivalent OGPA with at least two years research experience as evidenced from fellowship/ associateship/training/published papers etc.</p>

<p>b)Desirable: Experience in NGS data analysis.</p>

<p>Emoluments : Rs. 23,000/- per month + HRA (Masters Degree Holders)</p>

<p>Rs. 24,000/- per month + HRA (Ph.D Degree Holders)</p>

<p>Upper age limit : 40 years for Men &amp; 45 years for Women as on date of Interview (Upper Age limits are relaxable for SC, ST and OBC candidates as per Govt. of India norms (at present 5 years for SC/ST and 3 years for OBC)</p>

<p>Duration of Project : Till 31-03-2017.</p>

<p>Title of Assigment : Research Assistant (on contract basis)</p>

<p>No. of vacancy : One</p>

<p>Qualification : Essential : Post Graduation in Bioinformatics and  Minimum one year experience in NGS data analysis</p>

<p>Desirable : Experience in Perl/Python/R</p>

<p>Remuneration : Rs. 20,000/- per month (consolidated)</p>

<p>Scope of work :</p>

<p>1. Analysis of different file formats and their conversions.</p>

<p>2. Assessing the quality of data and filtering of raw reads.<br />3. Assembling the raw reads-de novo as well as reference  mapping.<br />4. Compression of aligned reads using Jam tools<br />5. RNA-seq. Analysis<br />6. Differential expression testing involving Normalization,  Statistical testing, heat map generation &amp; hierarchical  clustering<br />7. Annotating the assembled genome and geneet testing  and their validation<br />8. Metabolic pathway analysis<br />9. Comparative genomics<br />10. Setting up of genome browsers.</p>

<p>Period of Assigment : Initially for six months.</p>

<p>Date &amp; Venue of Interview : 21-05-2014 at IISR, Kozhikode at 10.00 AM</p>

<p>More at http://www.spices.res.in/pdf/disc-advtmnt.pdf</p>
]]></description>
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