MSc/PhD Program
Lawrence McKechnie
First Name:

Last Name:




Lawrence McKechnie


College / University:
University of Glasgow

Highest Degree:
M.Sc. (honours)

Major Subjects:
Molecular and Cellular Biology

Lab Experience:
Macromolecular modelling tools such as rasmol and pymol; generation of computer simulations using MATLAB; basic molecular biology/biochemical /genetic techniques; various bioinformatics tools and statistical packages

Projects / Research:
"The role of internal models in motor control", Prof. Stan Gielen, ”biophysics” research direction, Donders Institute, Nijmegen, the Netherlands
"Relationship between dihedral geometry of dipeptides peptides and their chemistry of action", Prof. James Milner-White, University of Glasgow
"Investigation into the application of nimbelgen micro arrays using PARTEK biostatistical software and DAVID bioinformatics tool", Dr. Pawel Herzyk, University of Glasgow
Investigation of "Possible roles of ras protein in receptor clustering of NMDA NR1 subunit", Wellcome Trust Sanger Institute, Genes2Cogntion project
Dissertation/literature review:  "The use of various computational methods to elucidate the meaning of the histone code", supervision: Dr. Brian Smith, University of Glasgow

2010 - 2011: Stipend of the Excellence Foundation for the Promotion of the Max Planck Society


I am deeply intrigued by how the brain can almost learn how to learn via trial and error, incorporating uncertainty into its representation of reality. This is a correspondence problem that has intrigued philosopher and scientist alike since the genesis of conceptual thought and can now be investigated using many of tools of modern neuroscience, an adventure I find extremely exciting.  This aforementioned feature of learning how to learn  is in contrast to a computer program that can be instructed to do various tasks in a deterministic manner. 
Currently, I am interested in research directions such as motor control, learning and memory (particularly epigenetic mechanisms), neural synchronization, bioinformatic approaches to brain evolution and computational/statistical analysis of biophysical aspects of neuronal function and possible neural mechanisms underlying the effect of mindfulness on depression.  I also believe that science has a strong societal dimension or inflection and, therefore, I think it is important to apply and invoke findings of scientific research in order
to understand the vectors of disease and psychiatric disorders, such as depression, anxiety to name but a few.
By participating in this program, I would like to put my understanding of biology into context and make the transition from a student into a researcher where my knowledge/understanding can be expressed through
the medium of research.  I hope to both deepen and widen my understanding of many diverse areas of neuroscience and also learn/practice integrative methods that can make many exciting, relevant questions answerable.