This post is written with some tongue-in-cheek; I do not mean for you to take these points as unassailable. No doubt there are some omissions here, but I had to pick my top ten (plus). These are things that looking back at my M.Sc. (Imperial) and D.Phil. (University of Oxford) experiences have forged the way I do scientific research, and built my academic character. My B.Sc. was too long ago to recall anything accurately! I find the exercise of writing them down useful (see the second commandment…).
These tips are mostly focused at writing an academic (and scientific) dissertation. But I think most of these suggestions are sensible enough they should feature in any lengthy document. Based on my experience as an examiner and a supervisor, these are the most common things I notice each time I pick a project write-up.
I see many students who struggle with LaTeX write-ups and who burn in typesetting hell for their mortal sins (hanging lists, anyone?). This post will focus on some of the more sophisticated details to publish a perfectly set document. This post is the first of a two-part series; focusing on LaTeX hints. The second part will focus on the actual write-up/content.
Some presentation tips, based on my experience of the things which trouble students (and for which they lose marks) and the things which irked me in previous study-units’ presentations.
So, you have contacted me to undertake a project (Dissertation/FYP/Thesis) together. That is Great! I am enjoying it already.
I always find myself repeating the same pointers to each student at the start (or throughout the project really). Thought I would write them down for posterity. So here comes my recipe for success, for the first few weeks at least.
My projects are typically on the life sciences/computer science interface (but we’ve had many different ones – including intelligent automated sports betting). But these three ingredients apply to any kind of project really.
I am always sending the same canned response to students who would like to do an FYP or a dissertation with me on the subjects I dabble in, Computer-Aided Drug Design (Discovery), Virtual Screening (VS), Ligand-based and Structure-Based methods, Cheminformatics, Bioinformatics and Computational Chemistry. Perhaps the first step for any student is to realize the hierarchy of these fields (and the differences between them). I am including a reading list – which helps you bootstrap the subject, and hopefully helps you determine if this is really something for you. The jargon will be daunting at first (especially if you are a computer scientist), but that is only an initial hurdle and hopefully you get familiar with the big words quickly. You do not need to understand everything, you just need to understand enough. Remember brick walls are there to show us how badly we want things! (Watch this: long and touching).
I often get the question “I’m interested in Bioinformatics but how do I get started?“. That question can typically be answered with “A google search“, but that is true for most of the non-existential questions nowadays. This post will give you pointers to material you need to cover to understand the basics of what this bioinformatics field is about. Unfortunately, there currently is no undergraduate/postgraduate course with focus on Bioinformatics (in Malta*) – so attending a series of (local) lectures is not an option presently. Do not despair, plenty of material to go around.
Note: This material is not specific to one area in bioinformatics, e.g. genomics, but aims to give a general (soft) introduction to the field!
It is that time of the year again. December, light drizzle, grey skies, Christmas presents lists, and of course progress reports for your B.Sc. final year project (FYP) or M.Sc. dissertation. So I understand the blank stares when students sit in front of LaTeX, wondering what they should write.
During our DataX course, we recently had an issue where installing the tm package had a dependency on the slam package (that’s Sparse Lightweight Arrays and Matrices for you). This package requires R >3.3.1, which is a shame as I asked students to install 3.2 at the beginning of the course. Don’t despair; keep calm and upgrade R.
As part of the TrainMALTA EU project activities, I volunteered/was tasked with setting up the IT infrastructure for the HTS (or NGS) bioinformatics summer school. It has been quite an experience, and the whole setup is far from trivial – so I thought I’d document parts of it here. Habitually, I turned to google to search what others in my shoes have done and nothing turned up. Nothing on google – this setup must be worth documenting!