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Capacity Building Efforts & Data Infrastructure at Makerere University and UVRI/Kitayibwa John

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Presentation during the Uganda National Dialogue on an Open Science Policy, 25-26 April 2018.

Published in: Data & Analytics
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Capacity Building Efforts & Data Infrastructure at Makerere University and UVRI/Kitayibwa John

  1. 1. Capacity Building Efforts & Data Infrastructure at Makerere University and UVRI Kitayimbwa John
  2. 2. Demand for Data Science • Big shortage of data science experts • Data literacy gap between (e-)infrastructure and data specialists • Core data experts need to be trained • Need to support training of data management experts • Possibly fund a concentrated effort to locate and develop data expertise in Uganda
  3. 3. Identified Data Science Competences
  4. 4. Identified Data Science Skills Skills/experience related to competences • Data Analytics and Machine Learning • Data Management/Curation (including both general data management and scientific data management) • Data Science Engineering (hardware and software) skills • Scientific/Research Methods • Application/subject domain related (research or business) • Mathematics and Statistics Big Data (Data Science) tools and platforms • Big Data Analytics platforms • Math & Stats apps & tools • Databases (SQL and NoSQL) • Data Management and Curation platform • Data and applications visualization • Cloud based platforms and tools
  5. 5. Identified Data Science Skills Programming and programming languages and IDE • General and specialized development platforms for data analysis and statistics Soft skills or Social Intelligence • Personal, inter-personal communication, team work (also called social intelligence or soft skills)
  6. 6. Identified Data Science Skills Data Analytics and Machine Learning Data Management/ Curation Data Science Engineering (hardware and software) Scientific/ Research Methods Personal/Inter- personal communication, team work Application/subject domain (research or business) 1 Artificial intelligence, machine learning Manipulating and analyzing complex, high-volume, high- dimensionality data from varying sources Design efficient algorithms for accessing and analyzing large amounts of data Interest in data science Communication skills Recommender or Ranking system 2 Machine Learning and Statistical Modelling for data improvement Big Data solutions and advanced data mining tools Analytical, independent, critical, curious and focused on results Inter-personal intra- team and external communication Data Analytics for commercial purposes 3 Machine learning solutions and pattern recognition techniques Data models and datatypes Multi-core/distributed software, preferably in a Linux environment Confident with large data sets and ability to identify appropriate tools and algorithms Network of contacts in Big Data community Data sources and techniques for business insight and customer focus 4 Supervised and unsupervised learning Handling vast amounts of data Databases, database systems, SQL and NoSQL Flexible analytic approach to achieve results at varying levels of precision Mechanism Design and/or Latent Dirichlet Allocation 5 Data mining Experience of working with large data sets Statistical analysis languages and tooling Exceptional analytical skills Game Theory 6 Markov Models, Conditional Random Fields (non)relational and (un)-structured data Cloud powered applications design Copyright and IPR 7 Logistic Regression, Support Vector Machines Cloud based data storage and data management 8 Predictive analysis and statistics (including Kaggle platform) Data management planning 9 (Artificial) Neural Networks Metadata annotation and management 10 Statistics Data citation, metadata, PID (*)
  7. 7. Bioinformatics in Uganda Research Networks collecting clinical, genetic & epidemiological data Training programmes such as MUII, BRECA & SIDA generating clinical mass of local talent HPC Infrastracture such as UMIC and ACEDIS Leveraging Potential of Big data and Bioinformatics in Uganda
  8. 8. • Sequencer (MiSeq) • 40 TB server • Analysis unit • eBioKit: Portable computer cluster Data Generated at both Makerere and UVRI
  9. 9. Computing Infrastructure (Cluster, Tele-learning Center, Virtual Reality) Center of Excellence in Bioinformatics & Data Intensive Sciences (ACEDIS) Housed at The IDI McKinnell Center, Makerere Univ.
  10. 10. Center participants (ACEDIS) ACEDIS MAKERERE (BRecA) NIH/OCICB IDI Will be a platform for: 1. Training 2. Research 3. Collaboration Housing and coordination Training + Research Hardware, Software, Virtual reality + other equipment
  11. 11. The Uganda Medical Informatics Centre (UMIC) Our data centre holds 42 Petabytes of data. That's 42,000,000,000,000,000 bytes. With that much storage you could listen to MP3 music for over 84,000 years
  12. 12. The Uganda Medical Informatics Centre (UMIC) • UMIC is situated at the Uganda Virus Research Institute • A high performance computing (HPC) and power stable cluster for performing bioinformatics and big data-related tasks • The UMIC cluster has a total of 2,048 cores and 16TB of RAM
  13. 13. Training
  14. 14. Nurturing Genomics and Bioinformatics Research Capacity in Africa (BRecA) PD/PIs Coordination & Key personnel Administration Presentation: D. Kateete & D. Jjingo
  15. 15. Training Advisory Committee (TAC) Local International
  16. 16. BRecA: builds on H3Africa supported activities in Uganda
  17. 17. BRecA Programme Objectives (1) To establish a Master’s program in Genomics & Bioinformatics that will produce a critical mass of skilled bioinformaticians. The MSc program will train ten students from Uganda and Africa (together with ENBiT) (2) To establish a Doctoral program in Genomics & Bioinformatics aiming to produce skilled scientists who can teach and perform independent genomics/bioinformatics oriented-research, responsive to African needs. Two students from Uganda and/or SSA will be trained (3) To provide postdoctoral training in bioinformatics that will enable two CAfGEN alumni (one Ugandan, one Botswanan) to transition into independent researchers (4) To establish a bioinformatics training center that will coordinate and oversee bioinformatics training at Makerere University
  18. 18. MAKERERE UNIVERSITY P.O. Box 7072 Kampala, Uganda E-mail: mbl@chs.mak.ac.ug Tel. 0414-541830 mjoloba@chs.mak.ac.ug COLLEGE OF HEALTH SCIENCES SCHOOL OF BIOMEDICAL SCIENCES Department of Immunology & Molecular Biology Curriculum for: MASTER OF SCIENCE IN BIOINFORMATICS (PLAN A) Approved by the Board of Research and Graduate Training - Makerere University March 2018 11.1. Curriculum Map CODE YEAR 1: SEMESTER I LH PH CH CU MSB7101 Molecular Biology for Bioinformatics 30 30 45 3 MSB7102 Bio-Conductor and R 30 30 45 3 MSB7103 Bio-Unix & Shell Scripting 30 30 45 3 MSB7104 Online Bioinformatics & Sequence Databases 30 30 45 3 MSB7105 High Throughput Sequencing and Analysis 30 30 45 4 MSB7106 Journal Club Series 1 0 0 0 0 TOTAL 16 CODE YEAR 1: SEMESTER II LH PH CH CU MSB7201 Molecular Evolution 30 30 45 3 MSB7202 Principles of Sequence Analysis & Phylogenetics 30 30 45 3 MSB7203 Bioinformatics Programming I 30 30 45 3 MSB7215 Journal Club Series 2 0 0 0 0 Electives (choose 2) MSB7204 Functional Genomics 30 30 45 3 MSB7205 Population Genetics and Genomics 30 30 45 3 MSB7206 Proteomics and Structural Biology 30 30 45 3 MSB7207 Disease Dynamics and Modelling 30 30 45 3 MSB7208 Bioinformatics Programming II 30 30 45 3 MSB7209 Epigenetics and Chromatin Remodeling 30 30 45 3 MSB7210 Bio-cluster Computing 30 30 45 3 MSB7211 Big Bio-data Analysis 30 30 45 3 MSB7212 Fundamentals of Biobanking 30 30 45 3 MSB7213 Metagenomics 30 30 45 3 MSB7214 Systems Biology 30 30 45 3 TOTAL 15 CODE RECESS SEMESTER: LH PH CH CU CHS8501 Scientific writing and dissemination 30 0 30 2 MSB7301 Responsible Conduct of Research 30 0 30 2 MSB7302 Bioinformatics Internship 5 TOTAL 9 CODE YEAR 2: SEMESTER I LH PH CH CU Approved by the Senate Board of Research & Graduate Training, Makerere University
  19. 19. MAKERERE UNIVERSITY P.O. Box 7072 Kampala, Uganda E-mail: mbl@chs.mak.ac.ug Tel. 0414-541830 mjoloba@chs.mak.ac.ug COLLEGE OF HEALTH SCIENCES SCHOOL OF BIOMEDICAL SCIENCES Department of Immunology & Molecular Biology Curriculum for: DOCTORAL DEGREE (PhD) PROGRAMME IN BIOINFORMATICS BY COURSEWORK AND DISSERTATION Approved by the Board of Research and Graduate Training - Makerere University March 2018 12.1. Curriculum Map CODE YEAR 1: SEMESTER I LH PH CH CU MSB7101 Molecular Biology for Bioinformatics 30 30 45 3 MSB7102 Bio-Conductor and R 30 30 45 3 MSB7103 Bio-Unix & Shell Scripting 30 30 45 3 MSB7104 Online Bioinformatics & Sequence Databases 30 30 45 3 MSB7105 High Throughput Sequencing and Analysis 30 30 45 4 TOTAL 16 CODE YEAR 1: SEMESTER II LH PH CH CU MSB7201 Molecular Evolution 30 30 45 3 MSB7202 Principles of Sequence Analysis & Phylogenetics 30 30 45 3 MSB7203 Bioinformatics programming I 30 30 45 3 Electives (choose 2) MSB7204 Functional Genomics 30 30 45 3 MSB7205 Population Genetics and Genomics 30 30 45 3 MSB7206 Proteomics and Structural Biology 30 30 45 3 MSB7207 Disease Dynamics and Modelling 30 30 45 3 MSB7208 Bioinformatics programming II 30 30 45 3 MSB7209 Epigenetics and Chromatin Remodeling 30 30 45 3 MSB7210 Bio-cluster Computing 30 30 45 3 MSB7211 Big Bio-data Analysis 30 30 45 3 MSB7212 Fundamentals of Biobanking 30 30 45 3 MSB7213 Metagenomics 30 30 45 3 MSB7214 Systems Biology 30 30 45 3 TOTAL 15 CODE RECESS SEMESTER: LH PH CH CU CHS8501 Scientific writing and dissemination 30 0 30 2 MSB7301 Responsible Conduct of Research 30 0 30 2 PHB9101 Doctorateness 30 0 30 2 PHB9102 Philosophy of Methods 0 0 0 0 TOTAL 6 Approved by the Senate Board of Research & Graduate Training, Makerere University
  20. 20. Acknowledgements EANBIT (Eastern Africa Network for Bioinformatics Training)

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