BOL: Related items

Bioinformatics Jokes !!

Jitendra Prajapati — Fri, 21 Aug 2015 01:26:54 -0500

Why was the Bioinformatics fired from his job?

A: He was getting too Sassy.

What did the bioinformatician say when he found out his team stopped using version control?

A: Y’all better Git!

Why did the computational biologist stay home from work?

A: He had a code!

Why was the bioinformatician's paper was rejected?

A: Journal thought it seemed scripted.

How can you tell that a Bioinformatics is working?

A: You can hear him Grunting!

Why bioinformatician always silence?

A: Because bioinformatician calmly whisper, “SSH”

Why was the bioinformatician always so sleepy?

A: He/She wasn’t given any Java.

Why did the program/software hanged?

A: Because genome float.

Why was the class upset that its parent died?

A: Because it wouldn’t be getting the inheritance!

Why did bioinformatician always works on the command line?

A: Because they don't want to scare you with huge amount of data!

Why did the bioinformatician attend the gay pride parade?

A: They supported polymorphism.

Why did bioinformatician prefer awk, PerlOneliner?

A: Because even computer can't handle to load the data.

Why don’t bioinformatician get along with others?

A: They’re too MEAN.

Why computational biologist are cool?

A: Because they are scripted!!

Why they talk $ unzip; strip; touch; finger; grep; mount; fsck; more; yes; fsck; fsck; umount; clean; sleep;

A: Ah, Ohhh, dude, these are *NIX commands

Did they really hack genome?

A: Yes, I guess so.

LSC: Improving PacBio Long Read Accuracy by Short Read Alignment

Abhimanyu Singh — Thu, 06 Sep 2018 16:27:35 -0500

Added Command line argument support.
Multi-stage execution modes.
Support for parallelization. Now execution proceeds in batches of long reads the size of which can be set by --long_read_batch_size N.
Better compressed intermediate files.
Added utilities folder.
Added support for multiple short read files.
Removed use of configuration file.

Address of the bookmark: https://www.healthcare.uiowa.edu/labs/au/LSC/

Essentials of Statistics and Data Analysis using R

Mon, 31 Aug 2015 01:32:12 -0500

Clinical Development Services Agency (CDSA) is an extramural unit of Translational Health Science and Technology Institute (THSTI), Department of Biotechnology, Ministry of Science & Technology, Government of India. CDSA has a national mandate of strengthening capacity and capability building in the area of Clinical development and Translational Research.

CDSA is pleased to announce a 4 days hands-on training program on “Essentials of Statistics and Data Analysis using R” at ICGEB, Aruna Asaf Ali Road, New Delhi on December 1 – 4, 2015. This will involve developing and enhancing skills to understand basic principles of statistics for summarizing data and use of appropriate statistical tests as well as providing an understanding of data analysis using R. Didactic lectures with practical sessions will be delivered by experienced faculties from AIIMS and Novartis. Live classroom with power point presentations, case studies, mock exercise, practical sessions on R, group work with time for discussion and Q&A sessions are added advantages of this workshop.

Please contact gayatrivishwakarma.cdsa@thsti.res.in or vineetabaloni.cdsa@thsti.res.in for program and registration details.

Please nominate personage or register yourself on or before November 6, 2015 along with the electronic transfer of registration fee.

pbmm2:A minimap2 frontend for PacBio native data formats

BioStar — Tue, 18 Feb 2020 03:36:22 -0600

pbmm2 is a SMRT C++ wrapper for minimap2's C API. Its purpose is to support native PacBio in- and output, provide sets of recommended parameters, generate sorted output on-the-fly, and postprocess alignments. Sorted output can be used directly for polishing using GenomicConsensus, if BAM has been used as input to pbmm2. Benchmarks show that pbmm2 outperforms BLASR in sequence identity, number of mapped bases, and especially runtime. pbmm2 is the official replacement for BLASR.

Address of the bookmark: https://github.com/PacificBiosciences/pbmm2

MetaPred2CS

Manisha Mishra — Fri, 03 Mar 2017 05:15:07 -0600

MetaPred2CS Web server is a meta-predictor based on Support Vector Machine (SVM) that combines 6 individual sequence based protein-protein interaction prediction methods to predict prokaryotic two-component system protein-protein interactions (PPIs). The methods implemented in MetaPred2CS are 2 co-evolutionary methods: in-silico two hybrid (i2h) and mirror tree (MT) methods and 4 genomics context based methods: phylogenetic profiling (PP), gene fusion (GF), gene neighbourhood (GN) and and gene operon methods (GO).

http://metapred2cs.ibers.aber.ac.uk/

Address of the bookmark: https://github.com/martinjvickers/MetaPred2CS

Understating pacbio reads name !

BioJoker — Fri, 23 Nov 2018 07:36:46 -0600

m140415_143853_42175_c100635972550000001823121909121417_s1_p0/553/3100_11230 0.99 24
└1┘└─────2─────┘└──3─┘└────────────────4────────────────┘└5┘└6┘└7┘└────8────┘└─9─┘└10┘

"m" = movie
Time of Run Start (yymmdd_hhmmss)
Instrument Serial Number
SMRT Cell Barcode
Set Number (a.k.a. "Look Number". Deprecated field, used in earlier version of RS)
Part Number (usually "p0", "X0" when using expired reagents)
ZMW hole number
Subread Region (start_stop using polymerase read coordinates)
readScore
barcodeScore

Bioinformatics Faculty at BHARATHIDASAN UNIVERSITY

Sat, 26 Sep 2015 20:34:20 -0500

BHARATHIDASAN UNIVERSITY

(Reaccredited by NAAC with ‘A’ grade)

TIRUCHIRAPPALLI - 620 024

I N V I T E S

APPLICATIONS FOR FACULTY POSITIONS UNDER UGC XII PLAN CREATED POSTS ON CONTRACTUAL BASIS TILL 31.03.2017 IN THE FOLLOWING UNIVERSITY DEPARTMENTS. (Notification No. 31300 /H2/2015, Dt.: 18.09.2015)

ASSISTANT PROFESSOR

1. Bio-Informatics ONE (MBC)

2. Bio-Chemistry ONE G.T.(W)DW

Consolidated Pay of Rs.45,000/- p.m.

Qualification : As per UGC/AICTE/NCTE norms

Application along with other details including specialization can be downloaded from the University website www.bdu.ac.in

LAST DATE FOR RECEIPT OF FILLED IN APPLICATION IS 07.10.2015 BY 5.00 P.M.

More Info : www.bdu.ac.in/adv/UGC_XII_Plan_Contract_Positions.pdf

INC-Seq: accurate single molecule reads using nanopore sequencing

Jit — Mon, 27 Nov 2017 10:38:56 -0600

INC-Seq reads enabled accurate species-level classification, identification of species at 0.1 % abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.

Address of the bookmark: https://github.com/CSB5/INC-Seq

R.A Bioinformatics at JNU, Delhi

Tue, 10 May 2016 01:50:38 -0500

R.A Jobs opportunity in Jawaharlal Nehru University (JNU) on purely temporary basis

Project Title : "Structural and functional characterization of serine biosynthetic pathway enzymes from Entamoeba histolytica"

No. of Post : 01

Qualification : Ph.D in any computational biology / bioinformatics

Desirable : 1. Experience with docking, simulations and structural biology with proof of publications is preferred. 2. National Eligibility Test cleared [CSIR/UGC] candidate is preferred.

Salary : According to CSIR rules
How to apply

The application on plain paper indicating name, date of birth/age, address, essential/technical/professional qualifications. experience, list of publications should reach The Prof. S. Gourinath, Principal Investigator, [Project Director], School of Life Sciences, Jawaharlal Nehru University, New Delhi-110067, on or before 23rd May 2016.

More at http://www.jnu.ac.in/Career/currentjobs.htm

HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads

Rahul Nayak — Tue, 08 May 2018 04:27:22 -0500

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs [Sirén et al. 2014], we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).

more at https://ccb.jhu.edu/software/hisat2/index.shtml

Address of the bookmark: https://github.com/infphilo/hisat2