MPhil in Computational Biology Handbook 2017-2018 PDF

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MPhil in Computational Biology Handbook 2017-2018

Contents 1.

Introduction ................................................................................................................................ 1

2.

Key Contacts 2017-18 ................................................................................................................ 1

3.

General Information ................................................................................................................... 2

4.

MPhil Calendar 2017/18 ............................................................................................................ 4

5.

Course Structure and Requirements ........................................................................................... 5

6.

Taught Modules 2017-18 ........................................................................................................... 6

7.

Internship ................................................................................................................................... 9

8.

Unfair means, plagiarism and collusion ................................................................................... 11

9.

Assessment and Examination ................................................................................................... 12

10.

Resolving difficulties ............................................................................................................... 15

11.

Guide for Internship Supervisors and Examiners .................................................................... 16

12.

Safety and Security .................................................................................................................. 18

13.

Departmental information ........................................................................................................ 19

14.

Library...................................................................................................................................... 20

15.

Email and Computing .............................................................................................................. 21

1.

Introduction

The MPhil in Computational Biology has been developed by the Cambridge Computational Biology Institute (CCBI) and is run by the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the Centre for Mathematical Sciences (CMS). DAMTP is one of two departments in the Faculty of Mathematics; the other being the Department of Pure Mathematics and Mathematical Statistics (DPMMS). The Faculty is part of the School of Physical Sciences. DAMTP is an unusually large department for its discipline with currently around 50 academic staff, about 85 postdoctoral staff and about 110 research students, supported by about 30 administrative, technical and secretarial staff. There are also around 250 students undertaking the Part III (MMath/MASt) degree which is run jointly by both DAMTP and DPMMS. The MPhil is based at the Centre for Mathematical Sciences in Clarkson Road, where there are lecture theatres, common rooms and a student computing room. This handbook provides administrative and other important information for MPhil students. In addition to this handbook there is a Moodle site which is the main repository for all materials, documentation and coursework submissions. Students will automatically be given access to both at the start of the academic year. See Section 3 – General Administration and Section 9 – Assessment and Examination for further information. 2017-18 Handbook: http://www.maths.cam.ac.uk/postgrad/mphil/currentstudents.html Coursework submission site on Moodle: https://www.vle.cam.ac.uk/course/index.php?categoryid=6181

2. Key Contacts 2017-18 Course Directors

Professor Simon Tavaré (G0.06, 60420) Dr Stephen Eglen (G0.11, 65761) Email: [email protected]

Director of CCBI

Dr Gos Micklem (G0.08, 60447)

Module Leaders

Dr Oscar Rueda (Functional Genomics) Dr Gos Micklem (Genome Informatics) Dr Aylwyn Scally (Genome Sequence Analysis) Dr Stephen Eglen (Scientific Programming) Dr Stephen Eglen (Computational Neuroscience) Dr Chris Illingworth (Population Genetics) Dr Stephanie Reichelt (Biological Imaging and Analysis) Dr Lorenz Wernisch (Network Biology) Dr Florian Markowetz (Cancer Evolution)

MPhil Students

[email protected] All MPhil students are subscribed to this list (see Section 15).

Course Administrator Graduate Office (C0.15, 37966) Email: [email protected]

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3.

General Information

Induction and preliminary courses At the start of the year you will be invited to attend an Induction Meeting in which administrative and other information about the course will be distributed. This year the meeting will take place on Monday 2nd October 2017. All students are required to attend this meeting. The Introduction to Molecular Biology will commence on Tuesday 3rd October and Introduction to Unix on the afternoon of Wednesday 4th October. A timetable will be circulated. If you are unable to attend this meeting for any reason, you must let the Course Administrator know. Lectures Most lectures will take place during University terms with lectures commencing on the first Thursday of full term (see Section 4 – Calendar for dates). Occasionally lectures may be scheduled outside of full term. Lectures are held in the Centre for Mathematical Sciences (CMS) unless otherwise stated. The timetable will be circulated at the start of term and provided at the Induction Meeting. It is also published on the Course Moodle and the Faculty’s website at www.maths.cam.ac.uk/lecturelists/. Any changes to the published timetable will be circulated to students by email at the earliest opportunity. The use of audio/visual recording equipment (e.g. ipods, cell phones) in lectures is not permitted without the prior consent of the lecturer. If you have a particular need to record lectures, other than taking notes, please contact the Course Administrator. Moodle All students and staff associated with the MPhil course will be given access to the Course Moodle at the start of the year. Moodle is the main repository for course materials and documentation. Weekly seminar and tea During Michaelmas and Lent terms a weekly seminar is held every Wednesday, 2-3pm in MR4. The seminars are not assessed, but are compulsory and you are expected to attend each week. A programme of speakers and their topics will be posted on Moodle. The seminar is followed by a weekly tea in the Pavilion G common room. This is a chance for you to meet informally with each other, speakers and members of staff. The aim of the seminar is to provide students with potential opportunities and resources that may not be provided by the taught modules. In particular the seminars provide an opportunity to meet local researchers who may well have research positions they want to fill, be it summer internships or PhD posts. Each week a researcher from Cambridge (either within the University, related academic sites or from local industry) will speak about their research. We aim to invite a diverse range of speakers from across the spectrum of Computational Biology to demonstrate the wide range of application areas, and we will ask for students to volunteer to host the speakers. Residence The MPhil is a full-time course which runs from October to the end of August. The last day of the course is 31st August. During term time students are expected to be resident in Cambridge. They may also be expected to participate in activities outside of term (which are principally set for the delivery of undergraduate programmes). Students should note that it is a requirement of the MPhil degree that they are resident in Cambridge for three terms. To keep residence they must attend for a certain number of days in each term. In order to meet the requirement for Easter, students whose internship is to be held outside of Cambridge must spend 53 nights in Cambridge between 10th April and 18th June (unless Full Term begins after 22st April, in which case between 17th April and 25th June). You may also need to apply formally for Leave to Work Away from the University. Please discuss this with the Course Administrator if you are uncertain if you will meet the requirement.

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Course representative Once you have had time to get to know one another we will ask you to elect a fellow student as a course representative. The role of the course representative is to provide feedback to us on any issues regarding the course, such as coursework and teaching. Further information will be circulated. Student Progress Each student will have the opportunity to meet individually with the Course Director once a term to discuss his/her progress. Information on how and when to sign-up for a meeting will be circulated. Further guidance on what to do if you encounter problems or difficulties can be found in Section 10 – Resolving difficulties. Student Feedback We encourage feedback from students on all aspects of the course. This helps us assess how well the course is running, and will help us to correct any current limitations. An online feedback questionnaire will be circulated at the end of each term asking for your feedback on the modules offered. All feedback is anonymous and you are encouraged to complete the questionnaire. The questionnaire responses will be sent to the relevant lecturers and to the Course Directors for consideration. In addition to this formal mechanism, we also encourage informal feedback at any time. Your comments regarding the course will be highly valuable to us in evaluating the content and direction of the course. As this area of computational biology is rapidly evolving, we expect to evaluate the content yearly to ensure that our students receive the best education possible in this field. Course Administration The Course Administrator is the main administrative contact for the MPhil (see Section 2 - Key Contacts). Any general questions you may have about the course should be directed to the Course Administrator in the first instance. The Course Administrator is part of the Mathematics Graduate Office team which is based in C0.15. In the Course Administrator’s absence please do not hesitate to contact any member of the team for assistance.

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4.

MPhil Calendar 2017/18 October Mon 02

Induction 11:00-12:30pm, MR15 Lunch 12:30 – 13:15, Pavilion G Common Room Tue 03 Full Michaelmas term begins Introduction to Molecular Biology, 10:00-12:00, MR15 Wed 04 Introduction to Molecular Biology, 10:00-12:00, MR15 Introduction to UNIX, 12:30 – 13:45, MR16 Thur 05 Michaelmas term teaching week 1 begins Introduction to Molecular Biology, 10:00-12:00, MR15 Wed 11 Seminars and weekly tea commence Wed 18 Deadline for submission of Turnitin acknowledgment form (online) (4pm) November Tues 28 1-to-1 meetings with Course Director this week December Fri 01 Full Michaelmas term ends January Tue 16 Full Lent term begins Weds 17 Internship meeting Thur 18 Lent term teaching week 1 begins Wed 24 Seminars and weekly tea commence March Fri 16 Full Lent term ends Students will be notified of which modules are to be examined in the general examination by the end of Lent Term April Tue 24 Full Easter term begins Thur 26 Easter term teaching week 1 begins May Fri 04 Deadline for submitting internship project titles/arrangements (4pm) Fri 11 MPhil General Written Examination (2-4pm) Mon 14 Internships begin June Fri 15 Full Easter Term ends August Wed 08 Deadline for submission of internship reports (4pm) Mon 13 Deadline for submission of internship presentation files (4pm) Wed 15 – Fri 17 MPhil Presentations (TBC) Fri 17 MPhil Oral Examinations where applicable September Fri 07 MPhil Examiners Meeting (TBC) Thur 20 Degree Committee Meeting October Sat 20 First available congregation for those graduating

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5.

Course Structure and Requirements

The modules to be offered in 2017-18 are as set out below. Candidates for the degree must offer all taught modules for examination, except that in Lent Term there is a choice between two half modules. All taught modules are assessed by coursework assignment. Normally students will be set two or three assignments for each module. Please see course outlines for details of forms of assessment. In addition, students sit a two-hour general examination in the Easter Term on the material taught within the modules. Students are also required to complete an internship project which is assessed by a report of no more than 18,000 words and a presentation. At the discretion of the Examiners, students may be required to attend an oral examination (see Section 9 – Assessment and Examination), The weighting for the examination in Computational Biology is out of 12, divided as follows: each module is weighted at 1, and half modules at 0.5, meaning a total weighting of 8 for the taught modules. The general examination is weighted at 1. The internship project is weighted at a total of 3, with 2.5 for the report and 0.5 for the presentation. Term

Module

Abbreviation

Weight

Michaelmas Functional genomics Genome informatics Scientific programming Genome sequence analysis (half module)

FG GI SP GSA

1 1 1 0.5

Lent

CE PG CN

1 1 1

Cancer evolution Population genetic analysis of genomic data Computational neuroscience Either Network biology (half module) or Biological Imaging and Analysis (half module)

NB

0.5

BI

0.5

Easter

Systems biology General Examination

SB EX

Summer

Internship Report Internship Presentation

IR IP TOTAL

1 1 2.5 0.5 12

Module Choices Most modules in the MPhil are compulsory. However, in Lent term students may choose to take either Network Biology or Biological Imaging and Analysis. Whilst students may attend lectures for any of these courses if they wish, they may only be formally examined for one of these two modules. The University sets the date by which students must make their choices and be formally enrolled for assessed modules. At the time of going to print this date has not been confirmed. Students will be informed by the Course Administrator of when they need to confirm their choices as soon as this information has been confirmed.

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6.

Taught Modules 2017-18

The following information provides a summary for each module offered in the current academic year. More detailed information will be provided by the module leader and lecturers as part of the course. Course materials and lecture notes will be uploaded by lecturers direct to the Course Moodle for students to access. Michaelmas Term

Functional Genomics (FG) Dr Oscar Rueda, Dr Rory Stark, Dr Maurizio Callari, Dr Geoff Macintyre and Rajbir Batra (Cancer Research UK Cambridge Institute), Dr Ernest Turro (Department of Haematology), Dr Shamith Samarajiwa (MRC Cancer Unit). Functional genomics looks at the dynamic aspects of how the genome functions within cells, particularly in the form of gene expression (transcription) and gene regulation. This class surveys current methods for functional genomics using high-throughput technologies. We cover all stages of the experimental workflow: experimental design and planning, pre-processing and quality control, normalization, differential expression, clustering, classification and survival analysis. We present workflows for the processing, quantification, and downstream analysis of microarrays, RNA-seq, CHiP-seq and methylation data as well as approaches that seek to integrate different data types. Assessment: Three assignments, weighted 30:30:40. The first two consist of an individual paper answering questions related to the lectures and practicals done during the course. The third assignment (40% of the final mark) has a group component (reproduce the analysis) and an individual component (extend the analysis). Students will be required to write a report and present the results in a 1 hour session. There will be a feedback session at the end of the course.

Genome Informatics (GI) Dr Gos Micklem (DAMTP/ Department of Genetics) Genome sequencing, sequence alignment and genome assembly. Genome annotation - genes, transcripts, proteins (functional annotation), non-coding DNA/RNA, repeats. Gene regulation. Sequence variation and the phenotypic consequences. Ontologies and databases. Assessment: Three assignments, weighted 20:40:40. The first and third assignments will be individual and assessed by written report, while the second will be a group assignment assessed by presentations.

Scientific Programming with R Dr Stephen Eglen (DAMTP) Interactive use of R. Basic data types. Writing scripts. Graphical facilities. Writing your own functions. File input/output. Vectorization. Numerics issues. Debugging. Reproducible research. Advanced aspects. Assessment: Three individual assignments. There will be a feedback session for each assignment after it is marked.

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Genome Sequence Analysis (GSA) Dr Aylwyn Scally (Department of Genetics) The course will introduce hidden Markov models, their properties, implementation and application to some important problems in bioinformatics and genomics. Topics: probabilistic models; Markov chains; hidden Markov models; inference with HMMs; the Viterbi algorithm; Baum-Welch training; sequence alignment. Assessment: A practical assignment in which students are required to implement and apply a computational HMM to genome sequence data and interpret its output. Lent Term

Cancer Evolution (CE) To follow

Population Genetic Analyses of Genomic Data (PG) Dr Chris Illingworth (Department of Genetics), Dr Aylwyn Scally (Department of Genetics), and Dr Richard Durbin (Welcome Trust Sanger Institute) Introduction to population genetics and evolutionary theory: basic evolutionary forces, mutation, genetic drift, recombination, and selection. More complex evolutionary scenarios. Inference of signatures of evolution from intra and inter-specific sequence data. Examples of evolutionary processes: cancer evolution, evolution of drug resistance. Quantitative models for understanding evolution experiments. Inference of selection in multi-locus systems. Inference of demographic histories of natural populations using sequence data. Assessment: Two written individual assignments, together comprising the whole of the mark for the course.

Computational Neuroscience (CN) Dr Stephen Eglen (DAMTP) and Dr Rafael Romero-Garcia (Department of Psychiatry) 1, 2. Introduction/Single neurons 3, 4. Short and long term memory/associative networks 5, 6. Complex brain networks 7, 8. Structure and dynamics networks 9, 10. Supervised learning 11, 12. Reinforcement learning 13, 14. Unsupervised learning 15, 16. Development of the nervous system Assessment: Two individual assignments, weighted evenly. There will be a feedback session for each assignment after it is marked.

Biological Imaging and Analysis (BI) Dr Stefanie Reichelt (CRUK CI) and Carola-Bibiane Schönlieb (DAMTP) Imaging Biological Processes has been revolutionized through the development of fluorescent probes and imaging systems which allow the observation of specific molecules and cell populations in time and within a whole organism. Before applying image analysis algorithms and mathematical analysis to biological questions, it is essential to understand the acquisition methods and also the biolo...