Practical tips on preparing and writing a dissertation for biomedical scientists

1. How to write a 1st class
dissertation on a laboratory
based honours project
Co-created by:
Lesley Stark: Reader, Cancer Biology
Nishan Brooks: Medical Sciences honours student
Freya Derby: Biomedical Sciences honours student
David Hayburn: Intercalating medical student

2. Ø Engage with your supervisor early regarding the
structure of the dissertation and communicate with
them throughout.
Ø Detail is key. In background information, data
analysis, statistics, figures, figure legends and
references.
Ø Don’t describe, analyse. Demonstrate knowledge of
why you did the project and each experiment, interpret
results, create arguments and defend conclusions.
Ø Write your dissertation as a story with all parts
linked.
Basic principles for gaining
top marks

3. Getting started
Ø Start early- the process will help clarify dissertation
structure and guide the final weeks of the project.
Ø Start by collating your data – the structure and focus
will depend on your results and the conclusions you
draw. Talk to supervisor at this point about structure.
Ø Check course handbook for guidelines on format.
Commonly abstract, introduction, materials and
methods, results, discussion and references.
Ø Start by focusing on components that give the most
marks - usually results and discussion.

4. David
How
m
uch
previous
understanding
should
I have
before
starting
the
project?
David
W
hen
should
I
start thinking
about the
structure
of m
y
dissertation?
• Most people have very little understanding of
the research area before starting their project.
Ask your supervisor for one good review and
a few key papers, then read these in a lot of
detail. Follow references for more reading.
Ask supervisor for clarification of areas you
don’t understand.
Student questions
• Start thinking about the structure and putting
pen to paper as early as possible. This will help
you identify any experiments that are essential
for firm conclusions to be drawn, before it is too
late. It also allows you to bring your own ideas
when discussing structure with your supervisor.

5. Freya
How
m
uch
weight
should
I give
to
individual
sections?
• The marks allocated to individual sections will be available in your
course handbook. However, usually the elements that show
analytical/critical thinking and problem solving (results and
discussion) gain most marks.

6. Results- Figure preparation
Ø A figure should contain all the data relevant to a
single significant finding.
Ø Compile figures using power point, adobe illustrator
or similar.
Ø Figure and legend should be self contained: The
reader should be able to easily extract all the critical
information just from the figure/legend.
Ø Figure legend: detail assays used, methods of
quantification, number of repeats and statistical tests
applied.
Ø Detail is important in figures (see next slide for a
checklist).

7. Figure checklist
1. Font should be consistent throughout. Usually Arial >8pt. Line widths no less
than 0.5pt and consistent.
2. Titles should be 8-10pt
3. Black and white images should be greyscale. Colour images in RGB
4. Put molecular weight markers on immunoblots. NB Include loading controls
5. Include scale bars on images. Mark features of interest clearly.
6. Avoid bar charts. Use box plots showing individual data points or line plots for
continuous data. NB use error bars where appropriate.
7. Clearly label axis on graphs.
8. Use colour wisely.
9. Export from powerpoint (or other design software) as max quality Jpeg and
insert into word at actual size
10. Figure legends:
Spell out all abbreviations
State assays and biological tools used to generate data
Include number of repeats for all experiments and all statistical tests
applied

8. Results- text
Ø Use one sub-heading per significant result.
Ø Each paragraph should start with why you did the
experiment, contain the experimental approaches you
took to answer the question, a brief description of the
results (highlighting the main points in the relevant
figure) and finally, what your conclusions are from that
experiment (see next slide for examples).
Ø Logical flow: Each paragraph should flow logically so
that the conclusion at the end of one signposts the
next question (Example on next slide).
Ø Don’t use vague terms such as “it appears to show”
or “it looks like is shows”. Be confident in your
interpretation.

9. Given that CBX4 has been known as a small ubiquitin-related modifier (SUMO) E3 ligase, we next examined
whether the ligase activity was required for the proliferation-promoting effect of CBX4 in hMSCs. Accordingly,
we constructed the lentiviral expression vector for wild-type CBX4 (CBX4-WT) and mutant CBX4 without
SUMO E3 ligase activity (CBX4-ΔSIM). The reintroduction of CBX4-WT or CBX4-ΔSIM alleviated various
aging defects observed in CBX4−/−
hMSCs (Figures 2J–2L), indicating that the SUMO E3 ligase activity of
CBX4 was irrelevant to the senescence-regulating effect of CBX4 in hMSCs.
To know whether premature MSC senescence caused by CBX4 deficiency is lineage specific, we
differentiated CBX4−/− and WT hESCs into human neural stem cells (hNSCs) (Figure S2A). Both WT
and CBX4−/−
hNSCs exhibited features of neural progenitors, including the expression of neural progenitor
markers Nestin, PAX6, and SOX2 (Figure S2B). However, distinct from CBX4−/−
hMSCs, CBX4−/−
hNSCs did
not exhibit premature senescent characteristics relative to WT hNSCs (Figures S2C–S2E). These results
indicate that CBX4 exerts an aging-regulating effect specifically in hMSCs.
Example of text
Rationale/question ConclusionProcedure/results

10. Freya
• The types of statistical tests you apply to your
data depends on the type of data that you
have generated, the number of repeats etc.
Speak to your supervisor or a specialist at
your institution for help.
Student questions
• Even a failed experiment is a result. Show you
understand why you did the experiment,
discuss the reasons why it may have failed and
steps you would take to optimise the
procedures or approaches in future.
How
do
youstatistically
analyse
your data?
W
hatshould
you
write
about
if you
get no
results?
Nishan

11. David
How
do
I talk
about negative
results in
a
positive
way?
All results, positive or negative, provide new understanding. Based
on your data and the literature, formulate an alternative hypothesis
to the one proven to be wrong, then describe experiments you may
do to test this new hypothesis.
Student questions

12. Ø Show critical thinking -For an explanation of critical
thinking see question from Nishan on slide 15 and
critical thinking stairway on slide 16.
Ø Start by drawing an overall conclusion from your
data and stating why this is important. i.e “I found--
-----. This is important because----------”.
Ø Bring data from different parts of the project
together to generate 2-3 conclusions. One or two
paragraphs per conclusion. Include; the data you
generated that supports the conclusion, how your data
and conclusion compare to published literature and
future experiments you would carry out to further test
your assumptions.
Discussion Do’s

13. Discussion Do’s (continued)
Ø Develop a model based on your data: using a
model to discuss your data can be useful.
Ø Construct arguments and use your own and other
people’s data to support or refute the argument. Part 4
of this video has good information on words to use
when building an argument:
https://www.youtube.com/watch?v=1hVNF_8S6Ok
Ø Have a paragraph discussing the limitations of your
data (if any).

14. Discussion dont’s
Ø Don’t just repeat the results.
Ø Don’t analyse each result individually in the order
they appear in the results section.
Ø Avoid phrases such as I think or I believe. The
examiner wants to know your opinion. Use phrases
like, my data suggests that, on balance the evidence
indicates that or, from my data it is not clear that.
Ø Extra marks are gained from relating your data
to literature unfamiliar to the examiners and
generating your own, new hypothesis

15. This is a very good question as it affects your academic success,
but it is not clear what it is.
See https://www.ed.ac.uk/institute-academic-
development/postgraduate/taught/learning-resources/critical for an
overview.
Developing your critical analysis worksheet (MS Word)
Basically, for the purpose of a dissertation, critical thinking is
demonstrating you can analyse and interpret complex data from
multiple sources and use in depth knowledge of a field to put this
data in context to generate new ideas (see next slide for more
info).
Student questions
W
hat is m
eant
by critical
thinking/insight?
Nishan

16. 8. Justify - Use critical thinking to develop arguments,
draw conclusions, make inferences and identify
implications.
7.Apply - Transfer the understanding you have gained
from your critical evaluation and use in response to
questions, assignments and projects.
6.Evaluate - Assess the worth of an idea in terms of its
relevance to your needs, the evidence on which it is based
and how it relates to other pertinent ideas.
5.Synthesise - Bring together different sources of
information to serve an argument or idea. Make logical
connections between the different sources that help you
shape and support your ideas.
4.Compare - Explore the similarities, differences between
the ideas you are reading about.
3.Analyse - Examine how these key components fit
together and relate to each other.
2.Understand - Comprehend the key points, assumptions,
arguments and evidence presented.
1.Process - Take in the information (i.e. in what you have
read, heard, seen or done).
Critical thinking ‘stairway’
The lower steps are the basics
that support moving to the
higher-level thinking skills that
underpin a critical approach.
Source: ‘Critical
thinking: online
guidance’, the Open
University (2009)
Critical thinking:
online guidance from
the Open University

17. Freya
How
do
you
start
researching
for your
discussion?
As soon as you start getting results, source papers that address
similar research questions using similar models. Question how their
data and experimental design compare to yours. This will help direct
further experiments, allow you to build in-depth knowledge of the
subject area and be aware of controversies in the field. By the time
you come to write your discussion you should have a library of papers
to draw on and be able to use your knowledge to interpret your data,
compare it to data in the field and generate new hypothesis.
Student question

18. Introduction
Ø Keep it concise and focused on the subject area of
the project (not a broad review).
Ø Provide rationale for undertaking the project (gaps in
knowledge) and set out research question(s). These
may have changed from the start of the project so
adapt to the question you answered.
Ø Keep acronyms to a minimum.
Ø Use figures to help explain complex
processes/pathways. Better self drawn.
Ø Finish by stating hypothesis and aims: 2-3 aims
max.

19. Additional components
Methods. Describe your experiments in a way
somebody could repeat them. This can involve
referencing other literature or lab web pages, but give a
brief description of all techniques used.
NB. Fully describe all methods of quantification and
statistical analysis.
Abstract. 1-2 sentences of background which highlight
gaps in knowledge. A sentence on the research question.
2-3 sentences on approaches and findings. 1-2
sentences on relevance and contribution to the field.

20. Additional components (cont)
Lay abstract. State the research question, results
and relevance in a way a member of the public could
understand.
How
lay
should
a lay
abstract
be?
Nishan
The important thing to note when writing a
lay abstract is to make it interesting. It
should not be a copy of the normal abstract
written in simpler terms. It should be a way
to engage the general public with the
research you are doing and what you have
found. This might only be the importance of
the research question, the absolute critical
finding and why this might be of relevance
to society.

21. Useful links
How to write a dissertation:
https://www.youtube.com/watch?v=1hVNF_8S6Ok
https://www.youtube.com/watch?v=1O_Go1KzAyE
https://www.thestudentroom.co.uk/showthread.php?t=1141163
Dissertation archive
https://www.era.lib.ed.ac.uk/handle/1842/3414