1. 1 Multidisciplinary Program in Computational Biology and Bioinformatics Biology / Agriculture Track CS Track Physics / Mathematics Track Initiated 2000 : 15 students /year Core Curriculum 1st year: Shared basis for all tracks (CS-Gen. Mol biol // LS- DS, Progr.,DB) Mandatory: bioinfo., comp. Struc. biol, practical in microarray algorithms in Mol Biol, Biotools & DB, seminar in comp. Mol Bio. 2nd year: Individual Curriculum, Thesis oriented (I.e ML, Structure, DB, Statistics, Genetics) Elective: transcriptomics, statistics, Complex systems, Learning, information, Protein World, Modelling… Research Thesis (flexible) wet work & bioinfo analysis (Medical, Agriculture) pure computational analysis. Algorithmic/ statistical based etc Tools and Technology developments HUJI Experience

2. 2 Multidisciplinary Program in Computational Biology and Bioinformatics Conclusions - HUJI (a personal view) Operatives 1. Experimental advanced wet lab is essential (exp. design, report..) 2. Shared advisors and mentors (2 disciplines) 3. Research Projects as a class summary / final grade 4. Reading Class & Bioclub (Let by Students) General 1. For CS/Physics students the assimilation of the complexity of biology is harder (too many details -not a clear picture) 2. For biologists acquiring the computational skills is easier. 3. Two majors in B.Sc. Levels - Highest success Initiated 1999. Top students. After 3 years: Majors: CS, Comp Biol and a division in Math (160 hr. hr=14 wk/semester) Already 55 Graduate Students 40 of them in MSc programs (30 in CB, 5 in LS, 5 in CS) ~15 in Industry etc. ~ 15 with two mentors. Direct PhD program MSc students are TA for research projects of 3rd yr students 4. Active participation in National/ International meeting (poster presenting…) Pitfalls and Hurdles 1. A Lag from previous study (working in Industry for few yrs) - very hard 2. Too little Maths 3. Level of interactions with Biologist & CS and Educational Stuff

3. 3 Multidisciplinary Program Questions - HUJI (a personal view) Common Ground? 1. The strength in CS ?? In Statistics?? In Biology?? In Maths/theory?? 2. Instructors vs group learning ?? (very good experience) 3. Condense class vs a semester length (longer is better) Adding disciplines of not? 1. Also physics? Also math? Also engineering ? (I.e., control system) 2. Importance - the research skills? The bioskills? Grades? Final Exams? 1. Shared material (BSc stuff) 2. Research presentation (defense) 3. Qualifying exam - a direct PhD program (2nd year) From Molecular Computation to System Computation? 1. Brain - Neuroinformatics 2. Developmental scheme 3. Population dynamics From Basic to Medical / Agriculture The Science of Technology (HTP)

4. 4 Multidisciplinary Program Rotations Ethics Lab regulation