Assimilate, Write, and Evaluate Reviews

Welcome to the course homepage of Review in Computational Biology, which will take place at Cambridge Computational Biology Institute, Centre for Mathematical Sciences, Wilberforce Road, Cambridge during Lent Term 2013.

The aim of this course is to develop two critical skills for research: the ability to identify relevant questions from the scientific literature and effective scientific writing. In addition, it introduces students to the process of publishing and peer reviewing of manuscripts. Every week, the course reviews a current research topic in computational biology. Each student will write one review, and provide two reports on colleagues' written work.

Lecturers Christophe Dessimoz and James Smith
Students 1st and 2nd-year PhD Students
Lecture Rooms & Times Every Wednesday Lent Term (Weeks 0 - 9), 14:00 - 15:00 CCBI Seminar in MR4, 15:30 - 16:30 Lecture in MR15
Supervisions (Tutorials) Supervision B Wednesdays 13:00 – 14:00, Supervision A Wednesdays 16:30 – 17:30
Course Doctoral Training Course Module


Published reviews initiated in this course

The following publications started as student assignment in this course, either at ETH Zurich (2010-2011) or University of Cambridge (2012-2013):

  1. A Szalkowski and C Schmid, Rapid innovation in ChIP-seq peak-calling algorithms is outdistancing benchmarking efforts, Brief Bioinform (2011) 12 (6): 626-633. (Link)
  2. C Ledergerber and C Dessimoz, Base-calling for next-generation sequencing platforms, Brief Bioinform (2011) 12 (5): 489-497 (Link)
  3. L du Plessis et al., The What, Where, How, and Why of Gene Ontology – A Primer for Bioinformaticians, Brief Bioinform (2011) 12 (6): 723-735 (Link)
  4. A Altenhoff and C Dessimoz, Inferring Orthology and Paralogy, Evolutionary Genomics: Statistical and Computational methods (M Anisimova, Editor), 2012, Springer Humana, Vol. 855, (Link)
  5. F Iorio et al., Transcriptional data: a new gateway to drug repositioning?, Drug Discovery Today (2013), 18:7/8, pp350-357, (Link)
  6. D Reker and L Malmström, Bioinformatic challenges in targeted proteomics, Journal of Proteome Research (2012), J. Proteome Res., 2012, 11 (9), pp 4393–4402, (Link)
  7. M Sunnåker et al., Topic Page: Approximate Bayesian computation, PLoS Comput Biol (2013), 9:1, e1002803 (Link)
  8. S Iantorno, K Gori, et al., Who Watches the Watchmen? An Appraisal of Benchmarks for Multiple Sequence Alignment, Multiple Sequence Alignment Methods (D Russell, Editor), Methods in Molecular Biology, 2014, Springer Humana, Vol. 1079 (arXiv, journal)
  9. Q Ul Ain, A Aleksandrova, FD Roessler and PJ Ballester, Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screening, WIREs Comput Mol Sci (2015). (link)
  10. M Ravenhall, N Škunca, F Lasalle, C Dessimoz, Inferring horizontal gene transfer, PLOS Computational Biology (2015), 11:5, e1004095 (