http://www.uib.no/rs/mcb

---how genetic variation is distributed within and between individuals,
---determining how this diversity changes over evolutionary time.

Hence, Cox group work at the interface between biology, statistics and computer science to address questions of outstanding biological importance through intrepretation of large genetic datasets.

Profile:
Associate Professor Murray Cox,
Inaugural Rutherford Fellow of the Royal Society of New Zealand, Principal Investigator in the BioProtection Research Center and Associate Investigator in the Allan Wilson Center for Molecular Ecology and Evolution
Email : m.p.cox@massey.ac.nz
Webpage: http://massey.genomicus.com/index.html

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;

Plants represent an untapped resource of natural bioactive compounds that significantly contribute to plant resilience to pathogens, herbivores, and abiotic stresses, and may be applied for medicine or crop protection. In this project, you will design and/or apply innovative omics integration strategies for genomics, transcriptomics, and metabolomics data, to discover plant specialized metabolite biosynthetic pathways and study their evolution. You will work together with the other PhD candidate in this project, which will entail a combination of algorithm development, greenhouse experiments, integrative omics analysis, and evolutionary genomics. Extensive local and international collaboration is foreseen, including possibilities for a foreign research visit as part of your PhD project.

The research is embedded within the chairs of Bioinformatics and Biosystematics. The projects will be (co-)supervised by Dr. Marnix Medema, Dr. Justin van der Hooft, Dr. Klaas Bouwmeester and Prof. Dr. Eric Schranz.

We ask

We are looking for two enthusiastic and complementary team players with all or a subset of the following skills:

a solid academic record (MSc) in bioinformatics, biology, or biotechnology
experience in computational omics analysis and proficiency in programming (in, e.g., Python)
at least basic to intermediate statistical and mathematical skills
demonstrable experience in working with next-generation sequencing data or with greenhouse experiments with plants
affinity with plant science, metabolism and/or biosynthetic pathways
you meet all the entry requirements of the WUR PhD programme.
More information

For more information about this position, please contact Marnix Medema, Associate Professor Bioinformatics, by email (marnix.medema@wur.nl).
For more information about the procedure, please contact vacaturemeldingen.psg@wur.nl.

The bioinformatics chat is produced by Roman Cheplyaka and hosted by Roman and Jacob Schreiber.

Address of the bookmark: https://bioinformatics.chat/

A research fellowship is available at the BioComputing Laboratory, University of Padova (URL: http://protein.bio.unipd.it/). A highly motivated and creative candidate is sought to work on structural bioinformatics. Specifically, the project entails the development of novel methods, tools and databases for the analysis of protein structures. The BioComputing Laboratory is a group of a dozen people working on several aspects of prediction of protein structure & function employing techniques at the intersection between biology, medicine, chemistry, physics & computer science. Our aim is to integrate the development of novel methods and their application to biologically relevant problems. We are looking for candidates with a solid Bioinformatics background, programming experience (Python, Perl, C++ and/or Java) and good knowledge of molecular biology (protein structure/function, signalling pathways). Candidates should have a degree with top marks, optionally hold a PhD, and be highly motivated to work on interdisciplinary research. Good knowledge of English, an open-minded spirit, being collaborative and creative are crucial. The fellowship, which should start in late 2013, is initially for one year. It will be commensurate to experience, can be extended depending on performance and may lead to a PhD degree. The successful candidate will be located at the BioComputing Laboratory, University of Padova. Travel support for conferences and/or research visits abroad may be provided. To apply, please send your CV, a brief description of your research background and the names of two (or more) references to Prof. Silvio Tosatto (Email: silvio.tosatto@unipd.it).

Contact Person (Referent): Silvio Tosatto
Ref. E-Mail: silvio.tosatto@unipd.it
Tel: +39 049 827 6269
Fax: +39 049 827 6260
Group Web Page: http://protein.bio.unipd.it/

Job Description:F.No.11/10(1)/929 Qualifications: Candidates should have Ph.D. degree. If Ph.D. candidates are not available at least Post Graduate degree with GATE/NET qualification is a must. Walk-in-Interview on 19.12.2013 at 2.30 P.M. to 5.30 P.M .. at Maulana Azad National Institute of Technology: Bhopal For more details,please visit website:http://www.manit.ac.in/manitbhopal/Year2013/Recruitment/Contract_faculty/contract%20faculty%202013-2014.pdf

For more @ http://www.manit.ac.in/manitbhopal/Year2013/Recruitment/Contract_faculty/contract%20faculty%202013-2014.pdf

Web address @ :http://www.manit.ac.in

ECM3413 - Bioinformatics

Contents

General Information

Lecture Slides

Past Exam Paper

Continuous Assessments

Suggested Reading List

General Information

	This module runs in Semester 2.
	It is taught by Dr Ed Keedwell (Module Coordinator)
	Module Descriptor:  ECM3413
	Lecture Times: Tuesday 5pm,  171| Thursday, 171
	Workshop Times: Wednesday 11am Blue Room (Weeks 29,33 &40)
	Assessment: 2 CAs each worth 15% | 1 Examination worth 70%

Lecture Slides (if you have to print slides, to save your ink choose 'print in black and white' on the print menu)

	PPT|PDF| Lecture 1 - Introduction to Bioinformatics (& Biology)
	PPT|PDF| Lecture 2 - Genome Sequences: from fragments to sequences
	PPT|PDF| Lecture 3 - Sequence Alignment 1
	PPT|PDF| Lecture 4 - Global Pairwise Sequence Alignment
	PPT|PDF| Lecture 5 - Local Pairwise Sequence Alignment (Smith-Waterman & BLAST)
	DOC| Workshop 1 - Using BLAST and other Bioinformatics Databases
	PPT|PDF| Lecture 6 - Multiple Sequence Alignment
	PPT|PDF| Lecture 7 - BLAST (in more detail) & FASTA
	PPT|PDF| Lecture 8 - Sequence Alignment Conclusion & Other Sequence Analyses
	PPT|PDF| Lecture 9 - Markov Chains and Intro to Hidden Markov Models
	PPT|PDF| Lecture 10 - Hidden Markov Models
	PPT|PDF| Lecture 11 - Classification in Bioinformatics
	DOC|Workshop 2 - Using See5
	Workshop Data - Part 1 - adult.names | adult.data | adult.test, Part 3 - wdbc.names| wdbc.data
	PPT|PDF| Lecture 12 - Gene Expression Data
	PPT|PDF| Lecture 13 - Decision Trees and Gene Expression Classification
	PPT|PDF| Lecture 14 - Other Methods for Gene Expression Classification
	PPT|PDF| Lecture 15 - Gene Regulation
	PPT|PDF| Lecture 16 - Neural Networks in Gene Expression Analysis
	PPT|PDF| Lecture 17 - Genome Analysis
	PPT|PDF| Lecture 18 - Conclusion/Revision Lecture

For some reason best known to itself, my PDF creator doesn't like the slide with the substitution matrix on.  Therefore this has been removed from Lectures 3 and 7 for the PDF copy only - however, more information on these matrices can be found here.

Past Exam Paper

The paper from 2007/8 can be found here.

Continuous Assessments

	PDF|  CA1 - Manual Sequence Alignment
	PDF|Promoter.names|Promoter.data|ML.names|ML.data| CA2 - Data Mining in Bioinformatics

Suggested Reading List

General Bioinformatics

<="top">Xiong, J., (2006) Essential Bioinformatics, Cambridge University Press

	Lesk, A.M., (2002) Introduction to Bioinformatics, Oxford University Press
	Higgs, P.G., (2005) Bioinformatics and Molecular Evolution,  Blackwell Publishing

Machine Learning in Bioinformatics

	Baldi, P., Brunak, S., (2001) Bioinformatics: The Machine Learning Approach, MIT Press
	Keedwell, E., Narayanan, A., (2005) Intelligent Bioinformatics: The Application of Artificial Intelligence Techniques to Bioinformatics Problems, Wiley

Professor/Senior Lecturer of Comparative Genomics
Vacancy Ref: 153610
Salary: Professor, Grade 10 will be within the Professorial range and
subject to negotiation
Senior Lecturer, Grade 9, 57,696 - 64,914 per annum

The School of Biodiversity, One Health and Veterinary Medicine has an
exciting opportunity to appoint a Professor/Senior Lecturer in Comparative
Genomics. You will make a substantial and positive contribution to the
strategic direction of the School/College through leading and contributing
to research of international standard, high quality teaching at both
undergraduate and postgraduate level, securing research funding, and
providing academic leadership and management within the School/College.

Applications are invited from candidates of international standing with
an appropriate record of academic achievement in comparative genomics
and associated omics technologies. We are looking for a candidate who
will complement our existing strengths in clinical veterinary medicine,
evolutionary biology, and animal physiology, with a demonstrable interest
in using domestic mammals among their study systems. We are particularly
interested in applications from candidates with a track record of
studying health related traits and their underlying genomic basis in
companion animals. Traits of specific interest include those related
to metabolism, ageing, and disease (e.g. cancer, autoimmune diseases,
neuromuscular disorders).

The School of Biodiversity, One Health and Veterinary Medicine is home to
researchers studying organismal biology and animal health across a diverse
range of systems, approaches and disciplines with existing strengths
in infectious disease, physiology, ageing, veterinary epidemiology, and
evolution among others. You will be based on the University of Glasgow's
Garscube campus, where the majority of veterinary teaching and research
infrastructure is located. This includes the Small Animal Hospital (a
recent 15M investment) and our Veterinary Diagnostic Services, offering
excellent opportunities for collaborative research at the clinical and
translational interface, especially with respect to companion animals.

We welcome applications from candidates with a Scottish Credit and
Qualification Framework level 12 (PhD) in animal biology, genomics and
health or related discipline with an extensive and established reputation
in research and significant teaching experience within the subject area.

This post is full time and open ended.

Visit our website for further information on The University of
Glasgow's, School of Biodiversity, One Health & Veterinary Medicine,
https://www.gla.ac.uk/schools/bohvm/

Informal Enquiries should be directed to Professor Roman Biek,
Roman.Biek@glasgow.ac.uk

Apply online at:
https://my.corehr.com/pls/uogrecruit/erq_jobspec_version_4.jobspec?p_id=153610