<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/22961?offset=30 https://bioinformaticsonline.com/poll/view/22920/how-long-have-you-been-a-bioinformatics-scientist-for Tue, 23 Jun 2015 10:55:33 -0500 https://bioinformaticsonline.com/poll/view/22920/how-long-have-you-been-a-bioinformatics-scientist-for <![CDATA[How long have you been a bioinformatics scientist for?]]> Most of the researcher have been a scientist whole life, but infact they actually started paying  it with at certain time.So, how long have you been in bioinformatics domain now?

]]> Jit https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio Mon, 25 Apr 2016 16:22:28 -0500 https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio <![CDATA[Venn Diagrams on R Studio]]> First step: Install & load “VennDiagram” package. 
# install.packages('VennDiagram')
library(VennDiagram)

Second step: Load data

Add filepath if “catdoge.csv” is not in working-directory.

d <- read.csv("catdoge.csv")

Address of the bookmark: http://rstudio-pubs-static.s3.amazonaws.com/13301_6641d73cfac741a59c0a851feb99e98b.html

]]> Jitendra Prajapati https://bioinformaticsonline.com/opportunity/view/41043/postdoctoral-scientist-genome-analytics-genome-bioinformatics-mf Sun, 16 Feb 2020 02:57:40 -0600 <![CDATA[Postdoctoral scientist genome analytics/ genome bioinformatics (m/f/*)]]> https://www.uksh.de/jobs/Stellenangebote-nr-20190570-p-8.html
Your profile:
Degree in bioinformatics, biostatistics, or equivalent
Experience in the processing and analysis of large-scale genomics data using compute clusters / high-performance computing
Strong competence in working in Unix/Linux environments (shell)
Strong programming skills (in particular: Python, R, Perl)
Experience with using git and snakemake
Fluent English language skills, both spoken and written
Strong communication skills and motivation to work in a young, interdisciplinary, dynamic team

Additional Information:

If you have any questions about scientific aspects of this position, please contact Prof. Lars Bertram, head of LIGA (lars.bertram@uni-luebeck.de).

Please contact Ms. Anna Wolbert for further questions about administrative details (recruiting@uksh.de).

Weitere Informationen erhalten Sie auch unter www.uksh.de/karriere.

Wir freuen uns auf Ihre Bewerbung bis zum 15.03.2020 unter Angabe unserer Ausschreibungsnummer 20190570.119.CL.

]]> https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data Wed, 23 Jul 2014 07:29:14 -0500 https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data <![CDATA[COSMOS, our workflow management system for NGS data]]> COSMOS, our Python-based management system for implementing large-scale parallel workflows focusing on, but not restricted to, large-scale short-read "NGS" sequencing data is open-access published via Advance Access in Bioinformatics (Gafni et al. 2014).  It is also available for download for non-commercial academic and research purposes at:

 http://cosmos.hms.harvard.edu/.

Address of the bookmark: https://cosmos.hms.harvard.edu/

]]> Jit https://bioinformaticsonline.com/news/view/19087/dcgor Sat, 08 Nov 2014 14:54:28 -0600 https://bioinformaticsonline.com/news/view/19087/dcgor <![CDATA[dcGOR]]> An R package for analysing ontologies and protein domain annotations has been published in PLoS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1003929). The package is distributed as part of CRAN (http://cran.r-project.org/package=dcGOR), and also at GitHub for version control.

The dedicated website is available in http://supfam.org/dcGOR, from which several demos are also provided:

1. Analysing SCOP domains: http://supfam.org/dcGOR/demo-Fang.html

2. Analysing Pfam domains: http://supfam.org/dcGOR/demo-Basu.html

3. Analysing InterPro domains: http://supfam.org/dcGOR/demo-Customisation.html

 

]]> Martin Jones https://bioinformaticsonline.com/blog/view/22995/bioinformatics-phd-postdoc-job-rejection Thu, 02 Jul 2015 08:52:46 -0500 https://bioinformaticsonline.com/blog/view/22995/bioinformatics-phd-postdoc-job-rejection <![CDATA[Bioinformatics PhD / PostDoc / Job Rejection]]>

While your PhD or PostDoc application, it is more common that you got rejected by many professors. Don't disappoint reply it calmly.

image

In grad school, I shared a house with three Bioinformatics PhD students. One, when he applied to a particular professor, received a letter that said, essentially, "If you are applying because you want to enrich yourself, great. If you are applying because you want a job, you should know that you won't get one." I am trying to tell you this is because if you, with a good background in Bioinformatics, are passing up opportunities, you must be a strong candidate in many areas. Enrich yourself.

So, my suggestion is take a deep breath, forgot about all. Don’t take it personally. It's been usual processes while hunting for a good lab and professor. Take is positive, I am not sure why they reject, but don't worry perhaps the lab don't deserve you. Always remember there are billions of reasons not to hire someone for projects, especially in a research sector.

My suggestion, please do not whine about how you were a great research candidate for the post, and you just can't understand why they were so stupid as to have rejected you! This feeling will not win you any points in research, community. Especially, when in todays socially connected era everyone is linked. Remember, a nice E-mail saying, "I really wished to working with you on this project and I hope we cross paths again," is all you need to send to the professor. Send a thank you note to the professor. Thank them for the time they spend to judge you. In the future, If you and the professor (of your dream) are attending a bioinformatics conference, invite him/her to lunch (please remember to pay the bill). In today evolving scientific ere, always remember to build your solid network in order to get a job of interest. Join all possible networking sites like LinkedIn, ResearchGate, Acamedia, FB for the same reason. You as a researcher always build a bridge with student/researcher/colleague/professor who have the research potential to lead in research and hire you. Just because you didn't get this project, doesn't mean there isn't another that will open up in couple of month.

Mostly, jobs that are hard to get are hard to get. Only you can decide if the continued sacrifices are worth the expected payout. If it is, keep on plowing. Build relationships. Attend conferences.

Image ref @ JaSonYa

]]> Jit https://bioinformaticsonline.com/bookmarks/view/26319/n50plottingtools Mon, 08 Feb 2016 15:39:04 -0600 https://bioinformaticsonline.com/bookmarks/view/26319/n50plottingtools <![CDATA[n50PlottingTools]]> Tools to create plots showing N-statistics for genome assemblies

More at https://github.com/dentearl/n50PlottingTools

Address of the bookmark: https://github.com/dentearl/n50PlottingTools

]]> Jit https://bioinformaticsonline.com/bookmarks/view/26424/biotoolbox Fri, 19 Feb 2016 09:14:44 -0600 https://bioinformaticsonline.com/bookmarks/view/26424/biotoolbox <![CDATA[BioToolbox]]> This is a collection of libraries and high-quality end-user scripts for bioinformatic analysis, including working with gene annotation, collecting data scores from a variety of modern file formats, and conversion between file formats. The Bio::ToolBox libraries provide a unified, abstracted interface to multiple common gene annotation formats and the collection of data from multiple data files. They rely on BioPerl SeqFeature libraries and related adaptors to access binary file formats including Bam, BigWig, BigBed, and USeq. The Bio::ToolBox package includes scripts for setting up databases of annotation, collecting annotated features, collecting genomic data relative to features, manipulating and analyzing data, and data format conversion.

More at http://cpansearch.perl.org/src/TJPARNELL/

Address of the bookmark: http://cpansearch.perl.org/src/TJPARNELL/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/30901/ideoplot Mon, 13 Feb 2017 09:47:32 -0600 https://bioinformaticsonline.com/bookmarks/view/30901/ideoplot <![CDATA[Ideoplot]]> Simple ideogram plotting and annotation in R.

Basic usage:

Rscript Ideoplot.R --heatmap hm.bed --annotate annotations.bed --out ideogram.pdf
-or-
Rscript Ideoplot.R --annotate annotations.bed

Options
  --ideobed, i      A bed file of reference contig lengths/chromosome names
  --heatmap, -h     Fill chromosomes with normalized heatmap
                   (described below)
  --annotate, -a    Add character annotations.
  --out, -o         PDF output name.
  --stripes, -s     Specify a file containing the layout of the
                    annotations (description below)
  --bars, -b        Add track annotations
  --reference, -f   Either hg19, or hg38
  --topdown, r      Flag, when set, flips the orientation (P arms
                    drawn on top).

Address of the bookmark: https://github.com/mchaisso/Ideoplot

]]> Shruti Paniwala https://bioinformaticsonline.com/pages/view/35805/python-learning-resources-for-bioinformatics-and-computational-biologist Fri, 02 Mar 2018 06:54:15 -0600 https://bioinformaticsonline.com/pages/view/35805/python-learning-resources-for-bioinformatics-and-computational-biologist <![CDATA[Python learning resources for bioinformatics and computational biologist !]]> Python is a general-purpose language, which means it can be used to build just about anything, which will be made easy with the right tools/libraries.

Professionally, Python is great for backend web development, data analysis, artificial intelligence, and scientific computing. Many developers have also used Python to build productivity tools, games, and desktop apps, so there are plenty of resources to help you learn how to do those as well.

For pros and cons visit http://www.bestprogramminglanguagefor.me/why-learn-python and http://bioinformaticsonline.com/discussion/view/459/python-vs-perl

More resources at https://github.com/CodementorIO/Python-Learning-Resources

Following are the list of useful python programming resources:

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