Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
1 Bioinformatics at Norwegian University of Science and Technology Professor Finn Drabløs Department of Cancer Research and Molecular Medicine Finn Drabløs – Bioinformatics 2 NTNU key figures 53 departments in 7 faculties NTNU Library Museum of Natural History and Archaeology 58 000 student applications a year – of which 9000 have NTNU as their first choice 20 000 registered students, 7000 admitted/year 3000 degrees awarded a year 220 doctoral degrees awarded a year 4320 employees 2600 empl. in education and research; 555 professors Budget: NOK 3.6 billion 555 000 m2 owned and rented premises NTNU, May 2006 3 Organizational chart BOARD RECTOR INFORMATION DIV. TECHNICAL DIV. ORGANIZATIONAL DIV. FINANCIAL DIV. UNIVERSITY LIBRARY STUDENT & ACAD. DIV. MUS. NAT.HIST. & ARCHEOL. FACULTIES ARCHITECTURE & FINE ART ARTS INFORM. TECH., MATHEMATICS & ELECTR. ENG. ENGINEERING SCI. & TECHN. MEDICINE NATURAL SCI. & TECHN. SOCIAL SCIENCES & TECHN. MAN. NTNU, May 2006 4 Department of Computer and Information Science Research groups • Algorithms, HPC and Graphics (Networks, Evolutionary methods) • Computer Architecture and Design (FPGA) • Database Systems (Databases for biobanks) • Design and Use of Information Systems • Information Management (Data integration, Text mining) • Information Systems • Intelligent Learning Arenas • Knowledge-Based Systems • Logic and Language Technology (Ontologies) • Self-Organizing Systems • Software Engineering 5 GeneTools / eGOn 6 Department of Cancer Research and Molecular Medicine DNA Repair and Genome Stability • Molecular Biology (mainly related to DNA repair) • Proteomics • Structure Biology (X-ray) • Microarrays (printed, Affymetrix) / Genotyping (Illumina) • Bioinformatics • Interagon (Bioinformatics company) 7 Function is context-sensitive Uracil DNA glycosylase involved in both DNA repair and somatic hypermutation 8 FUGE – Functional Genomics • National program for functional genomics – Technology platforms – Research projects • FUGE I 2002-2006 • FUGE II 2007-2011, 420 MNOK • Application deadline April 18, 18:00 – Several technology platforms • • • • Bioinformatics technology platform (extension) Microarray technology platform (extension) Biobank technology platform (extension) … – Several research projects • miRNA in cell cycle regulation • Genome Browser – statistical module (Ensembl) • … 9 HUNT • The Nord-Trøndelag Health Survey – HUNT 1 - 1984-1986 • Health survey - 75.000 participants (20+) – HUNT 2 - 1995-1997 • Health survey + blood - 65.000 participants (20+) • Health survey - 9.000 participants (13-19) • 46.000 participated in both HUNT 1 and HUNT 2 – HUNT 3 - 2006-2008 10 Cell cycle studies • • • • Cell cycle synchronised (G1) HaCaT cells Status measured with flow cytometry Triplicates at 12 time points (1.5 cycle) Measured with Affymetrix U133A and B – 2 x 22.000 probes • Processing – Regulated genes – Regulatory motifs – Network 100 S-phase 90 G1-phase 80 G2-phase 70 60 50 40 30 20 10 0 0 3 6 9 12 15 18 21 24 27 30 33 11 Bioinformatics research areas • Transcription factor and RNA based gene regulation – Finding regulatory motifs in co-regulated genes – Comparing regulatory regions • Structure prediction and modelling of protein structures Automatic ligand docking Potential ligand binding sites • Part of FUGE Bioinformatics platform 12 miRNA gene and target prediction • Ongoing research activity – FUGE project with University of Bergen, using zebrafish to verify prediction of regulatory features (promoters, enhancers, miRNA) • FUGE application: “The roles of microRNAs and transcription factors in gene regulation and tissue specific expression” – Includes cell cycle regulation, international collaboration 13 Composite motif discovery • Find motifs (binding sites) that tend to occur together • Use general “motif generators” for input – MEME, Pratt, Teiresias • Do exhaustive search with efficient search tree pruning for motif combinations with flexible distance and N-of-M matching Lecture Notes in Computer Science 2005 14 Contributions • Literature scanning, manual curation – Partly linked to FUGE technology platform • Experimental test bench, feedback on usage – Linked to projects on gene regulation • (Text mining on protein – protein interactions) • (Ontology data linked to e.g. microarray data) – (Medical ontologies with versioning)