Category Archives: News

Symposium on Big Data in Mental Health

flyer 140613

We are excited to announce our upcoming symposium on Big Data in Mental Health.

The event will be held at ORTUS, Denmark Hill, on July 23rd and highlights will include Maneesh Juneja, Chris Hollis from MindTech, Will Spooner from Eagle Genomics and speakers from the University of Oxford, KCL and SLaM.

See the event page for more details:

Registration on Eventbrite:


Algorithm design and strategy by Dr David Baker (Janssen). Implementation and application by Dr Steven Kiddle (KCL). For queries please contact steven.kiddle (at) kcl (dot) ac (dot) uk .


Pre-processing for Relative Quantification (PRQ) of TMT tagged LC-MS data is an R script written to pre-process mass spectrometry data. It performs the following steps:

Median normalisation to correct for labelling and MS-run variation (Step 1) is performed within each sample and gel fraction. This involves calculating the median of the ratios of all peptide intensities from one sample versus the corresponding intensities measured in the reference sample. All intensities relating to that sample and gel fraction are then divided by the median ratio. Ratio scores for each peptide are then calculated (Step 2) by calculating the ratios of the normalised data for each peptide by dividing it by the reference intensity. Ratios corresponding to the same source protein, peptide sequence and gel fraction are then summed. Protein level data is derived from these summed peptide scores (Step 3) by taking either the mean or median of all peptide scores from the same source protein and gel fraction. This protein level data is then collected across all sixplexs (Step 4).

A paper describing and applying PRQ has been submitted.

Open source script and readme available here


Post Doctoral Researcher in the application of Digital Technology

Post Doctoral Researcher in the application of Digital Technology

King’s College London

We are looking for an experienced Post Doctoral Researcher in the application of Digital Technology to Mental Health.

In the digital era we generate more data every 2 days than we did in the time up until 2003. This big data is being used by advertising, media, retail, finance and travel with medicine and healthcare lagging behind. The data held in electronic patient records and generated through modern digital devices are examples of the big biomedical data that we could use to develop more targeted treatment strategies. So, the challenge in e- and m- health is no longer data generation, the problem has shifted to data handling and the separation of signal from the noise to produce clear indicators of whether a clinical intervention is necessary. This is especially an issue in mental health as we work with less clear signals.

The exciting opportunity is now to use new technology to support more sophisticated models which might detect signals early enough to provide opportunities for effective interventions that keep people well.

This post will be based in our established BRC informatics group and work with the Patient and Carer Theme to develop shared informatics tools and infrastructure to enable data harmonization and analytics for use in discovering the personal signatures for needs for care using machine learning for example.

The role will contribute to the growing initiatives within the BRC clinical informatics, bioinformatics and biostatistics groups ( whose others areas of focus include integrating genomics with electronic hospital patient records and cloud based patient owned records such as MyHealthLocker.

The post-holder will have an established track record in programming on the Linux OS, and will ideally also have quantitative research skills and/or previous experience of working with digital health data although this is not essential.

The post is funded for 18 months and the salary is grade 6 on King’s salary scale, currently £31,644 -£37,756 plus London allowance of £2323 per annum.

For an informal chat pleas contact Dr Richard Dobson,; Prof Til Wykes,

To apply, please go to

Consent, Ethics and Data Security Workshop

We had a great turnout for last Thursday’s workshop looking at issues around using clinical data in research. I hope everyone who attended found it as useful as I did.

Someone asked for a copy of the worksheet from the morning session, so I’ve uploaded it here: Data Management Questions

Huge thanks to all of the speakers. I have uploaded slides to our slideshare account: and linked to them below. I’ll upload summaries of the breakout sessions later this week.

If you have any questions or comments about the workshop, feel free to drop us an email or comment on this post.

Artificial Intelligence in Mental Health

NIHR Biomedical Research Centre for Mental Health, and NIHR Biomedical Research Unit for Dementia

Institute of Psychiatry – Institute of Psychiatry

Location: London
Salary: Not specified
Hours: Full Time
Contract: Contract / Temporary
Placed on: 15th May 2014
Closes: 19th June 2014

King’s College London

To start: October 2014

We are offering a PhD studentship to applicants with background in Computer Science, particularly Artificial Intelligence or Multi-agent systems. The award is funded by the National Institute for Health Research (NIHR) through the Biomedical Research Centre for Mental Health (BRC-MH) and Biomedical Research Unit for Dementia (BRU-D) at South London and Maudsley NHS Foundation Trust (SLaM) and the Institute of Psychiatry, King’s College London (KCL).

The BRC-MH and BRU-D are pioneering multidisciplinary translational research and experimental medicine in the areas of mental health and neuroscience. They bring together researchers, clinicians and allied health professionals from the UK’s largest NHS mental health service provider (SLaM), and the Institute of Psychiatry (IOP), the largest academic community in Europe dedicated to the study, treatment and prevention of mental health problems and neurodegenerative disease. The IOP offers excellent opportunities for research training in basic and clinical science across the mental health spectrum on one campus, with further strong links with our BRC partner at Guy’s, King’s and St Thomas’ hospitals.

The aim of the project is to evaluate the use of multi-agent computer systems in guiding the clinical decision making process for improved patient care. The project involves designing and implementing a fully workable multi-agent environment responsible for complementing the decision making process. The proposed system will actively monitor entries made to the patient electronic health records through the Electronic Patient Journey System (EPJS) in the aim of anticipating and minimising the occurrence of adverse events, providing evidence-based clinical advice, enforcing adherence to clinical guidelines and capturing and reporting data entry mistakes and clinical errors. The outcome of the project is an active monitoring and guiding system to be incorporated into EPJS, which results less inconsistencies and enforces prompt response to critical events.

How to apply

Click here (  for entry requirements, award details and eligibility, further information about the IOP, BRC-MH and BRU-D, and how to apply.