Bioinformatics postgraduate personal statement example

Personal statement example

In the second term of my final-year project I had a spreadsheet with ninety-six coloured cells, one for each well of a qPCR plate, and a growing suspicion that my plate layout mattered more than my pipetting. My project measured expression of two stress-response genes in a cultured epithelial cell line after heat exposure. When I compared runs, one plate gave consistently higher values for every sample, treated or not. My supervisor suggested I look at batch effects, and that phrase sent me into a part of biology I had barely met in lectures.

Until then my statistics had been the minimum the course required. To understand what was happening I taught myself enough R to import the raw cycle threshold values, normalise them against two reference genes using the delta-delta Ct method, and plot each plate separately. Seeing the offset as a picture, rather than a column of numbers, made the problem obvious, and I redesigned my final runs so every plate contained samples from each condition. The biological result was modest, a clear increase in one gene and an inconclusive change in the other, but the part of the write-up I was proudest of was the methods section explaining why the earlier data could not simply be pooled. My project mark was among my best, and the experience convinced me that I want to work where wet-lab questions meet careful computation.

Since graduating I have worked in specimen reception in a hospital pathology laboratory. The job is not glamorous: I log samples, check labels against request forms and route tubes to the right section. It has taught me how much depends on metadata. A missing collection time or a mislabelled tube can make a perfectly good sample unusable, and I now think about data provenance in a very practical way. I have also become the person colleagues ask when the tracking spreadsheet misbehaves, and I wrote a small set of formulas that flags duplicate entries at the end of a shift, which my supervisor adopted.

Alongside work I have been building the skills a bioinformatics course will demand. I completed a free online Python course and worked through the exercises on Rosalind, which gave me a feel for sequence problems such as counting nucleotides, finding motifs and translating open reading frames. I have read parts of Bioinformatics and Functional Genomics by Jonathan Pevsner, especially the chapters on pairwise alignment and BLAST, and I now understand why scoring matrices and gap penalties change which matches are reported. I am honest that my programming is still at an early stage; I can write working scripts, but I want structured training in algorithms, version control and analysing large sequencing datasets, which I cannot get from self-study alone.

Outside the laboratory I help on Tuesday evenings at a children's code club in my local library. Explaining loops to ten-year-olds using Scratch has made me better at breaking problems into steps, and occasionally at admitting I need to check something before answering. I also run parkrun most Saturdays, and I keep a slightly over-engineered record of my times in R, which is how I first learned to use ggplot properly.

I am applying for postgraduate study because I want to move from noticing problems in data to being able to solve them rigorously. I am particularly interested in transcriptomics, having come at it through a very small qPCR experiment, and I would like to understand how the same questions about normalisation and batch effects scale up to RNA sequencing. I bring laboratory experience, a habit of checking where data came from, and the persistence to learn programming in my own time. I would like the chance to turn those into genuine expertise.