Under   a   NEPAD   initiative,   the   Biosciences   Eastern   and   Central   Africa   (BECA)  (www.biosciencesafrica.org) was established at ILRI. BECA consists of a hub, regional nodes, and  other affiliated laboratories and partner institutes. A state of the art joint Bioinformatics Platform  (www.becabioinfo.org), whose overall goal is to provide a coherent and powerful bioinformatics  infrastructure for use by all scientists in East and central Africa. The Platform goal requires both  physical and intellectual developments that together provide researchers with access to diverse  infrastructure in a wide­area network, thereby addressing four important aspects of bioinformatics: 

1) Science: bioinformatics tools for data integration and visualization, standardization of data  formats and data analysis strategies, and distribution of analysis tasks over local­ and widearea networks are in development; 

2)  Bioinformatics Support Facility: provides assistance and custom programming to projects  and those unable to establish a bioinformatics support function intrinsic to their project due  to shortage of qualified personnel or lack of funding; 

3) Hardware Platform: provide a powerful high performance computing platform capable of  handling the largest analysis needs for projects; 

4) Bioinformatics Training for East and central African scientists: While many Web­based  tools are available to the wet­lab researcher, the Web is not well suited for tasks beyond  single­sequence annotation. Researchers need to become productive in a server­based Unix  environment with its wealth of scripting and automation tools. Even at an entry­level, this  can be an intimidating task if proper guidance is not available.

International Centre of Insect Physiology and Ecology (ICIPE): ICIPE’s research focus is on insect biology, in order to improve the wellbeing of the peoples of the  tropics through insect science. There is a commitment to utilise contemporary science in order to  limit the impact of disease vectors, and agricultural pests. The understanding of the mechanisms  associated with behaviour (e.g. attraction and repellency) is crucial. ICIPE seeks to enhance its  bioinformatics capacity in order to support data from various EST projects designed to gain insights  into the insect ecology and plant pathogen interactions though studies of metabolic pathways  associated with production of all elochemicals. 

Long­term training activities:

Kenyatta University: An introductory course in Bioinformatics is offers to MSc Biotechnology  students. This comprises of 35 hours of lectures and practicals.

University of Nairobi: A centre for Biotechnology and Bioinformatics (CEBIB), which will offer  postgraduate training (diplomas, MSc and PhD) in areas of biotechnology and bioinformatics has  recently been launched. Other universities in Kenya, including Egerton, Maseno and the Jomo Kenyatta University of  Agriculture and Technology offer introductory courses to undergraduates in biomedical sciences. In addition, under the BECA platform MSc and PhD fellowships are being made available for  Bioinformatics students. ILRI is forging links with Universities in South Africa and the United  Kingdom to provide access to courses and training material. 

Research Interest and Activities:

The following are the present areas of research interest: 1. EST clustering 2. Genome sequencing and annotation 3. Functional genomics and proteomics (including key tropical pathogens) 4. Structural bioinformatics 5. Development of Bioinformatics Data Management Systems 6. Gene Mining 7. High Throughput Genotyping 8. Microarray data management and analysis 9. Metagenomics 10. Immunoinformatics 11. Host­pathogen interaction 12. High performance computing and grid development 13. Parasite transfection technologies 14. Cell cycle regulation 15. Population genetics 16. Vector genomics 17. Drug, vaccine and diagnostic target discovery

More at Web site and links:

http://www.ilri.cgiar.org/

http://www.icipe.org/    

http://www.uonbi.ac.ke/cebib

Centre de Biotechnology de Sfax (CBS):
Bioinformatics activity started at CBS in 2001 with the setting­up of a research and service unit of  bioinformatics. This unit currently includes one senior researcher, one engineer and four Phd  students. Activities include sequence annotation (service) and three research programs: ab initio  prediction of short eukaryote genes, statistical modelling by Bayesian networks approach of signal  transduction pathways and statistical analysis of human sequence variation data (haplotype  reconstruction and linkage disequilibrium). Activities of the Bioinformatics unit could be found at  the website: http://www.cbs.rnrt.tn/ and the research activity report is available under request to  Bioinformatics@cbs.rnrt.tn. Although the computing facilities are good, there is still a need for  trained human resources to strengthen bioinformatics capacities at CBS, particularly in structural  bioinformatics.

Web site and links: http://www.cbs.rnrt.tn

Understanding DNA-protein interactions, genome engineering
Computational Genomics and Bioinformatics
Secondary metabolite biosynthesis, metabolic engineering

Ongoing Projects:

"Betraying the parasite’s redox system: Studies on spermidine synthase of Leishmania donovani "

"Towards modifying nature's DNA-recognition system"

"Yield enhancement strategies for production of therapeutic compounds by cell and tissue cultures of Tinospora cordifolia (willd.) Miers ex Hook. F. & Thoms"

"Program support for Computational Genomics"

More at http://web.iitd.ac.in/~sundar/

The group is both computational and experimental.

We ask biological questions to large datasets made using novel genomics techniques, with the help of computers. One of the strengths in the group are the many connections to high-profile experimental laboratories which supply data to be analyzed.

Lab webpage @ http://people.binf.ku.dk/albin/Sandelin_group_at_the_Bioinformatic_Centre/The_Sandelin_group.html

Gene expression and protein expression patterns between normal and non-normal tissues is a growing area of research that may lead to the identification of candidate genes for understanding the etiology of common, complex diseases.

Lab homepage @ http://ritchielab.psu.edu/ritchielab/

Available immediately until 30th November 2015, to work on the development of bioinformatics approaches to aid analysis of data derived from the metabolomic profiling of biological matrices. The successful applicant will lead research activities on an FP7 funded EU-wide collaborative project aimed at establishing biomarker-based strategies for high throughput diagnostic screening. Key tasks will involve multivariate analysis of large datasets, bioinformatic-based selection and validation of identified markers, construction of metabolomic spectral profile databases and development of machine learning/database searching approaches amenable to analytical screening techniques. This position will offer the opportunity to travel and undertake work with project collaborators based in the Republic of Ireland and Europe.

Informal enquiries may be directed to Dr Terry McGrath, email: terry.mcgrath@qub.ac.uk.

Anticipated interview date: Thursday 31st October 2013
Salary scale: £30,424 – £39,649 per annum (including contribution points)
Closing date: Monday 21st October 2013

Telephone (028) 90973044 FAX: (028) 90971040 or e-mail on personnel@qub.ac.uk

The University is committed to equality of opportunity and to selection on merit. It therefore welcomes applications from all sections of society and particularly welcomes applications from people with a disability.

Fixed term contract posts are available for the stated period in the first instance but in particular circumstances may be renewed or made permanent subject to availability of funding.

More @ https://hrwebapp.qub.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=5616943npO&WVID=6273090Lgx&LANG=USA

To fully leverage these opportunities, bioinformaticians require specialized tools and databases. This blog highlights essential resources for mycology research, focusing on databases, tools, and platforms tailored for fungal biology.

1. Fungal Databases

1.1. MycoCosm

Website: MycoCosm
Developed by the DOE Joint Genome Institute, MycoCosm is a comprehensive portal for fungal genomics. It offers genomic and transcriptomic data for a wide range of fungi, including saprobes, pathogens, and symbionts.

• Key Features: Genome browsers, comparative genomics tools, and functional annotations.
• Best For: Large-scale studies on fungal evolution and ecology.

1.2. FungiDB

Website: FungiDB
FungiDB is an integrated genomic resource for fungal pathogens and non-pathogens. It provides access to genome sequences, transcriptomic data, and functional annotations.

• Key Features: Advanced search options, BLAST, and pathway analysis tools.
• Best For: Studying fungal pathogenesis and host-pathogen interactions.

1.3. Index Fungorum

Website: Index Fungorum
This nomenclatural database provides information on the scientific names of fungi. It’s an essential resource for taxonomists and researchers focused on fungal biodiversity.

• Key Features: Taxonomic hierarchy and synonymy tracking.
• Best For: Identifying and classifying fungal species.

1.4. UNITE

Website: UNITE
UNITE is a specialized database for fungal ITS (Internal Transcribed Spacer) sequences, often used in fungal identification and phylogenetics.

• Key Features: Curated reference datasets and community annotations.
• Best For: Environmental mycology and microbial ecology studies.

2. Analytical Tools

2.1. Funannotate

Repository: GitHub - Funannotate
Funannotate is a genome annotation tool designed for fungi. It supports tasks like gene prediction, functional annotation, and orthology analysis.

• Best For: Annotating newly sequenced fungal genomes.

2.2. BUSCO (Benchmarking Universal Single-Copy Orthologs)

Website: BUSCO
BUSCO evaluates genome assembly and annotation completeness using orthologs. It includes a fungal-specific dataset.

• Best For: Assessing the quality of fungal genome assemblies.

2.3. Pathogen-Host Interactions Database (PHI-base)

Website: PHI-base
PHI-base is a manually curated resource containing information on pathogen-host interactions, including fungal pathogens.

• Best For: Exploring virulence factors and host-pathogen relationships.

3. Visualization Platforms

3.1. Cytoscape

Website: Cytoscape
A powerful tool for visualizing molecular interaction networks, Cytoscape can be used to study protein-protein interactions, gene networks, and metabolic pathways in fungi.

• Best For: Network biology and functional genomics.

3.2. iTOL (Interactive Tree of Life)

Website: iTOL
iTOL is an interactive tool for visualizing phylogenetic trees.

• Best For: Displaying fungal phylogenies and comparing evolutionary relationships.

4. Community Resources

4.1. Mycological Society of America (MSA)

Website: MSA
The MSA promotes fungal research and provides access to resources, conferences, and publications.

• Best For: Networking with fungal researchers and accessing recent studies.

4.2. OpenFungi

Website: OpenFungi
OpenFungi is an open-source initiative providing fungal genomic and transcriptomic datasets for research and education.

• Best For: Sharing and accessing public fungal datasets.

5. Genomics Workflows

5.1. Galaxy

Website: Galaxy Project
Galaxy offers a web-based platform for reproducible bioinformatics workflows, including tools for fungal genome and transcriptome analysis.

• Best For: User-friendly analysis pipelines without requiring coding skills.

5.2. Snakemake

Repository: Snakemake
A flexible pipeline management tool that supports fungal data processing and analysis.

• Best For: Custom workflows for large-scale fungal datasets.

Conclusion

Fungal research is a rapidly growing field with vast implications for medicine, agriculture, and industry. For bioinformaticians, the availability of specialized resources—databases, tools, and community platforms—opens doors to innovative discoveries. Whether you are investigating fungal genomics, studying host-pathogen interactions, or exploring fungal biodiversity, the resources outlined above will empower your research journey.

Dive into these resources and help unravel the mysteries of the fungal kingdom!

Deadline for applications : January 15, 2014.

Description :

We seek a talented and motivated post-doc to develop computational methods for inferring the molecular basis of genetic diseases by integration of personal omics data. Research topics include: identifying causal mutations of rare disease patients by meta-analysis; inferring disease-causing molecular pathways from genotype, human phenotypes, and omics profile of patient-derived cell lines; and causal inference from longitudinal omics studies of patients. The developed methods will be applied to analyze data from our medical collaborators.

Candidates must either hold a PhD in computational biology or bioinformatics, or hold a PhD in physics, statistics, or applied mathematics with practical experience with high-dimensional data analysis. Experience in quantitative genetics is a plus. Applicants must have a proven publication record and an interest for translational research.

The Gagneur lab is a young, lively and multidisciplinary group with a research focus on systems genetics and gene regulation. It is located at the Gene Center of the LMU (University of Munich), an interdisciplinary institution whose 16 independent research groups investigate the regulation of gene expression at all levels - from the underlying molecular mechanisms to the biological system. The institute is located on the biomedical research campus Munich-Grosshadern, offering a dynamic, interactive and internationally oriented research environment. The dynamism of Munich and the proximity of the Alps provide an excellent quality of life.

The salary is according to the TV-L (German academic salary scale).
Applications including a cover letter, CV, and references must be sent by January 15th 2014 to Julien Gagneur (gagneur@genzentrum.lmu.de)

About the lab: http://www.gagneur.genzentrum.lmu.de

Problem :

The CG island is a stretch of DNA (usually longer than 200 bases) in which the frequency of the CG sequence is higher than other regions. It is also called the CpG island, where "p" simply indicates that "C" and "G" are connected by a phosphodiester bond.

CpG islands are often located around the promoters of housekeeping genes (which are essential for general cell functions) or other genes frequently expressed in a cell. At these locations, the CG sequence is not methylated. By contrast, the CG sequences in inactive genes are usually methylated to suppress their expression. The methylated cytosine may be converted to thymine by accidental deamination. Unlike the cytosine to uracil mutation which is efficiently repaired, the cytosine to thymine mutation can be corrected only by the mismatch repair which is very inefficient. Hence, over evolutionary time scales, the methylated CG sequence will be converted to the TG sequence.

Find step wise explanationand implementation steps at http://dna.cs.byu.edu/bio465/Labs/hmm.shtml

Source code with explanation http://www.tannerhelland.com/1187/hidden-markov-models-viterbi-algorithm-cpg-islands-in-vb6/

Fore detail understanding of HMM read this excellent tutorial http://www.cs.ubc.ca/~murphyk/Software/HMM/labman2.pdf

Viterbi Algo at http://en.wikipedia.org/wiki/Viterbi_path

For firther reading Wiki page http://en.wikipedia.org/wiki/Hidden_Markov_model

On CpG island paper and for indepth understanding http://www.biomedcentral.com/1471-2164/12/S2/S10

If you are more interested in exploring Markov Chain Exploration and understand it with graphical version please visit http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=75049&lngWId=1

Reference:

1.http://www.planet-source-code.com

2. http://www.tannerhelland.com

the study of the sequence-structure relationship
(application -> structure prediction)
the study of the structure-function relationship
(application -> function prediction)

Therefore, anything related to the configuration (sequence) and conformation (structure) in atomic systems of proteins and nucleic acids, and the interaction of these with other elements (function) is of our major interest.

Lab page @ http://melolab.org/mbl/