University of Ibadan (UIB)­Ibadan:
There has been significant increase in the number of bioinformatics activities in Nigeria (and West Africa) since 2003 when the program was initiated by the West African Biotechnology Workshops Series (WABWS, http://www.wabw.org) at the University of Ibadan, Nigeria (in collaboration with  the South African National Bioinformatics Institute (SANBI, http:/www.sanbi.ac.za). Workshops  that were open to scientists from all African countries have seen a very high number of applications  from scientists based in West Africa. The encouraging desire to acquire cutting­edge skills to  computational process data and extract useful knowledge from genome projects led to the interest of  the West African Biotechnology Workshops (WABW) to develop an agenda to address the  bioinformatics skills gap among scientists in West Africa. An increased commitment from agencies  like NEPAD would be required in the provision of infrastructure to establish and sustain regional  and national networks.

University of Ilorin (UIL)­Ilorin:
The University of Ilorin was established in 1976 by the Federal Government of Nigeria.  Bioinformatics activities started at the University in February 2003 with the establishment of the  West African Bioinformatics Research Initiative (WABRI). However, progress has been rather slow  due to inadequate funding. We are mainly engaged in Bioinformatics training at the introductory  level and proteomics studies on various species of malaria parasites. Recently, we became interested  in comparative genome analysis of various species of  Plasmodium  and the comparison of  chloroquine sensitive and chloroquine resistant strains of Plasmodium falciparum. Other activities  and areas of interest can be seen on our website, http://www.wabri.org, although not all our  proposed interests have been fully implemented due to our level of funding.

Training:
The University of Ilorin has introduced M.Sc. and Ph.D. programmes in Computer Science (with  options in Bioinformatics). The programme is based in the Department of Computer Science and  emphasis is on the development of algorithms to solve problems in bioinformatics. The Covenant University offers M.Sc. and Ph.D in Computer Science with option in Bioinformatics  (Computational Biology). Furthermore, through affiliated departments, the CBBM is been design to award Diploma and Degree certificates in Biotechnology.

Web sites and links: http://www.covenantuniversity.com http://www.run.edu.ng http://www.uniben.edu http://www.wabri.org http://www.wabw.org http://www.unilorin.edu.ng http://www.wabri.org http://www.asopah.org

Disclaimer: This cartoon is solely designed to create humour and fun, not to offend any PI, supervisor or student.

1) Senior Research Fellow under ICMR Project: M.Sc. (Life Sciences) with 2 years of experience (preferable in the field of Bioinformatics) or MBBS Degree.

2) Research Associate under ICMR Project: . Ph.D.(Life Science/Biotechnology/Bioinformatics) or equivalent degree or having 3 years of research, teaching and design and development experience after M.Tech with at least one research paper in science Citation Indexed (SCI) Journal.
Work experience in the area of Human genomics/Next Generation Sequencing data analysis/Big data genomics would be preferred.
Application link:

https://sgrh.com/joblist

Post Code: 2023, 2024

More at >> http://www.nottingham.ac.uk/deepseq/events.aspx

#NBGN21

www.nbgn21conference.com

Classificier of reads from metagenomic sequencing experiments.

•  Kawulok, J., Deorowicz, S., CoMeta: Classification of Metagenomes Using k-mers, PLOS ONE, 2015; 10(4):1–23,

CoMSA

Compressor of multiple sequence alignments of proteins.

•  Deorowicz, S., Walczyszyn, J., Debudaj-Grabysz, A., CoMSA: compression of protein multiple sequence alignment files, Bioinformatics, 2019; 35(2):22–234,

DSRC

Compressor of sequencing reads.

•  Roguski, L., Deorowicz, S., DSRC 2: Industry-oriented compression of FASTQ files, Bioinformatics, 2014; 30(15):2213–2215,
•  Deorowicz, S., Grabowski, Sz., Compression of DNA sequences in FASTQ format, Bioinformatics, 2011; 27(6):860–862,

FAMSA

Multiple sequence alignment designed for huge families of proteins (even containing hundreds of thousands of sequences).

•  Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., FAMSA: Fast and accurate multiple sequence alignment of huge protein families, Scientific Reports, 2016; 6(33964):

FaStore

Compressor of FASTQ files.

•  Roguski, L., Ochoa, I., Hernaez, M., Deorowicz, S., FaStore - a space-saving solution for raw sequencing data, Bioinformatics, 2018; 34(16):2748–2756,

FQSqueezer

Experimental high-end compressor of FASTQ files.

•  Deorowicz, S., FQSqueezer: k-mer-based compression of sequencing data, Scientific Reports, 2020; 10(578):

GDC

Compressor of collections of genome sequences.

•  Deorowicz, S., Danek, A., Niemiec, M., GDC 2: Compression of large collections of genomes, Scientific Reports, 2015; 5(11565):1–12,
•  Deorowicz, S., Grabowski, Sz., Robust relative compression of genomes with random access, Bioinformatics, 2011; 27(21):2979–2986,

GTC

Genotype databases compressor with support for fast queries.

•  Danek, A., Deorowicz, S., GTC: how to maintain huge genotype collections in a compressed form, Bioinformatics, 2018; 34(11):1834–1840,

GTShark

Genotypes compressor.

•  Deorowicz, S., Danek, A., GTShark: Genotype compression in large projects, Bioinformatics, 2019; 35(22):4791–4793,

KMC

Memory frugal k-mer counter.

•  Kokot, M., Długosz, M., Deorowicz, S., KMC 3: counting and manipulating k -mer statistics, Bioinformatics, 2017; 33(17):2759–2761,
•  Deorowicz, S., Kokot, M., Grabowski, Sz., Debudaj-Grabysz, A., KMC 2: Fast and resource-frugal k-mer counting, Bioinformatics, 2015; 31(10):1569–1576,
•  Deorowicz, S., Debudaj-Grabysz, A., Grabowski, Sz., Disk-based k-mer counting on a PC, BMC Bioinformatics, 2013; 14():Article no. 160,

Kmer-db

Tool for estimation of evolutionary distances in a collection of genomes.

•  Deorowicz, S., Gudys, A., Dlugosz, M., Kokot, M., Danek, A., Kmer-db: instant evolutionary distance estimation, Bioinformatics, 2019; 35(1):133–136,

MuGI

Index allowing queries for a collection of multiple genome sequences.

•  Danek, A., Deorowicz, S., Grabowski, Sz., Indexes of Large Genome Collections on a PC, PLOS ONE, 2014; 9(10):e109384,

ORCOM

Experimental compressor of sequencing reads.

•  Grabowski, Sz., Deorowicz, S., Roguski, L., Disk-based compression of data from genome sequencing, Bioinformatics, 2014; 31(9):1389–1395,

PgSA

Index allowing queries for a collection of sequencing reads.

•  Kowalski, T., Grabowski, Sz., Deorowicz, S., Indexing arbitrary-length k-mers in sequencing reads, PLOS ONE, 2015; 10(7):1–16,

QuickProbs

Multiple sequence alignment designed especially for GPU.

•  Gudys, A., Deorowicz, S., QuickProbs 2: towards rapid construction of high-quality alignments of large protein families, Scientific Reports, 2017; 7(41553):
•  Gudys, A., Deorowicz, S., QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors, PLOS ONE, 2014; 9(2):e88901,

RECKONER

Read error corrector.

•  Maciej Długosz, M., Deorowicz, S., RECKONER: read error corrector based on KMC, Bioinformatics, 2017; 33(7):1086–1089,

TGC

Compressor of collections of genomes given in Variant Call Format (VCF) files.

•  Deorowicz, S., Danek, A., Grabowski, Sz., Genome compression: a novel approach for large collections, Bioinformatics, 2013; 29(20):2572–2578,

VCFShark

Compressor of VCF files.

•  Deorowicz, S., Danek, A., GTShark: Genotype compression in large projects, biorxiv.org, 2020; ():

Whisper

Experimental mapper of whole genome sequencing data.

•  Deorowicz, S., Gudys, A., Whisper 2: indel-sensitive short read mapping, bioRxiv.org, 2019; :
•  Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz., Whisper: read sorting allows robust robust mapping of DNA sequencing data, Bioinformatics, 2019; 35(12):2043–2050,
•  Deorowicz, S., Debudaj-Grabysz, A., Gudys, A., Grabowski, Sz., Robust mapping of whole genome sequencing data, Poster at The Biology of Genomes Conference, 2017;

Kindly log on to conference website http://rgcb.res.in/IACR2014 for further details and timely updates and registration. We shall truly appreciate if the same be circulated among your friends, scholars and students encouraging them to participate in the meet.

http://210.212.237.38/iacrconference/

2. Parallel sequencing lives, or what makes large sequencing projects successful https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false

3. Common-sense approaches to sharing tabular data alongside publication https://www.sciencedirect.com/science/article/pii/S2666389921002300

4. A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker https://psyarxiv.com/8xzqy/

5. Practical Computational Reproducibility in the Life Sciences https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6

6. A video by Dr.Keith A. Baggerly from MD Anderson [The Importance of Reproducible Research in High-Throughput Biology](https://www.youtube.com/watch?v=7gYIs7uYbMo) highly recommended.

7. Ten Simple Rules for Reproducible Computational Research http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285)

8. Good Enough Practices in Scientific Computing http://arxiv.org/abs/1609.00037 

9. Best Practices for Scientific Computing https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745

10. A Quick Guide to Organizing Computational Biology Projects http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042  A must read for computational biologists!

11. Reproducibility of computational workflows is automated using continuous analysis https://www.nature.com/articles/nbt.3780

12. Five selfish reasons to work reproducibly https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7

Software; Creation of Public Domain Resources in Biology
Present Status::

Developing prediction methods for gene, beta-turn, secondary structure and MHC-binding sites.
Area of Interest ::

Comparison of force field simulations. Analysis of DNA-protein interactions using molecular mechanics methods.Drug Target Identification using in silico biology.

More @ http://www.imtech.res.in/bic/index.php?option=com_content&view=article&id=65

PIs: http://www.imtech.res.in/bic/index.php?option=com_content&view=article&id=69