Dr James Smith
- Position: Lecturer in Biochemistry
- Areas of expertise: Metabolic & Biophysical Modelling, Molecular Data Science, Systems and Network Biology, Medicinal and Computational Chemistry & Biochemistry.
- Email: J.Smith252@leeds.ac.uk
- Phone: +44(0)113 343 1414
- Location: 7.65 EC Stoner
- Website: LinkedIn | Researchgate | ORCID
I joined the Chemistry & Biochemistry Section in the School in September 2016 as a University Lecturer in Biochemistry.
I completed my PhD in 2001 in Computer-aided Drug Design (Computational Medicinal Chemistry) from the University of Cambridge. During my postdoctoral research career, I have held posts at the University of Cambridge, at the University of Elrangen Nuremberg and as a Resaerch Fellowship at Jacobs University in Germany, then a temporary lecturer at Birbeck College London and UCL. then as an MRC Senior Investigator Scientist at the former MRC Human Nutrition Research, Elsie Widdowson Laboratory in Cambridge. I have also been a long-standing Affiliated Lecturer at the Cambridge Computational Biology Institute, DAMTP, University of Cambridge.
- School PGT Tutor and PGT Admissions
- Previously, NatSci Link Tutor - Joint Hons & NatSci committees and Progression & Awards Board.
- School Academic Lead for Inclusive Practice, Module Leader
- Iosifina Sampson and Richard Bayliss, University of Leeds – Structural & systems biology of cancer
- Valerie Speirs, University of Aberdeen – Experimental target validation in tumour cell lines
- Nick Parker and Andrew Baggaley, Newcastle University and DEFRA, HMGov UK – Mathematical biology of environmental epidemic spread
- Chi-Ying Huang, National Yang Ming University, Taiwan – Network biology in target prediction
- Garstka Malgorzata Anna, Xi'an Jiaotong University, Xi’an City, Shaanxi, PR China – Diagnostic biomarker discovery in early GDM.
- Ahmed M. Ibrahim, Mansoura, Dakahlia, Egypt – Potential adjustment of gut microbe populations with a pro-phylactic nutritional strategy for metabolic syndrome.
- Babiker Badri, Ahfad University for Women, Omdurman, Sudan – Natural product inspired re-design of anti-leishmanicidal agents.
- Nadia Hamdy, Ain Shams University, Cairo, Egypt – Natural product inspired docking
- Micheal J Wise, University of Western Australia – Computational and Mathematical Biology
- Albert Koulman and Davide Chiarugi, University of Cambridge. – Computational Biology
- Wuge Briscoe, University of Bristol – Physical Chemisry
- Co-I Wellcome Trust (London)-funded University of Leeds Institutional Strategic Support Fund Discipline Hopping Fellowship for Iosifina Sampson 2020-2021. With Lucy Stead and Richard Bayliss, University of Leeds and Mariko Okada, Osaka University.
- Modelling the structure and crystallisation of kidney stones EPSRC (Swindon) 2283981 2019
- Machine Learning Exploration of Circulating Biochemical Biomarkers for Gestational Diabetes Wellcome Trust (London) UNS89407 2019.
- British Council, Newton Funds, FAPESP (Brazilian Research agency) and ANII (Uruguayan Research Agency), UK, Brazil & Uruguay
Exploring the potential of biological soft matter in AgriFood challenges 2018.
- Co-I BBSRC DRINC BB/M027252/1 and BB/M027252/2 Validation of biomarkers of metabolic efficacy in infant nutrition with Albert Koulman, Core Metabolomics and Lipidomics Laboratory, University of Cambridge Metabolic Research Laboratories, UK.
Current and Previous PhD Students
- Riannnon Morris co-supervised with Helen Chappell, and Antonia Borrissova and Andrew Scott, University of Leeds.
- Oliver Hills co-supervised by Helen Chappell, and Deirdre Devine and Andrew Scott, University of Leeds.
- Yuwei Li (Bacterial spatio-temporal patterning and rock-paper-scissor dynamics in quorum sensing) co supervised with Francisco M. Goycoolea, University of Leeds
- John W. Holden (Lattice-based epidemic spread, and novel forecasting of disease velocities to inform effective containment strategies) with Nick Parker and Andrew Baggaley Newcastle University, and Melvin Holmes and Rammile Ettelaie University of Leeds, and kindly funded and co-supervised by Sam Grant, DEFRA (HMGov UK).
- Dr Nienyun Sharon Hsu (Revealing Putative Drug Targets for Basal-like Breast Cancer) previously jointly supervised with Richard Bayliss, University of Leeds. Now at the University of Sheffield.
- NIHR Grant Peer reviewer.
- European Commission H2020 Registered Expert Evaluator.
- Peer Reviewer for Computational & Mathematical Methods in Medicine, PLOS ONE, Journal of Theoretical Biology.
Local Recognition in Student Education
- Shortlisted for The Personal Tutor Award and The Supervisor Award, Faculty of Environment Partnership Awards 2021.
- Winner of The Personal Tutor Award and shortlisted for The Superivsor Award, Faculty of Environment Partnership Awards 2020.
- Shortlisted for The Inspirational Teaching Award, Faculty of Mathematics and Physical Sciences Partnership Awards 2018.
- Shortlisted for The Supervisor Award, Faculty of Mathematics and Physical Sciences Partnership Awards 2017.
- PhD, University of Cambridge, UK.
- BSc (Hons) Biological Sciences, University of Leicester, UK.
- The Biochemical Society (London)
- The Nutrition Society (London)
- British Biophysical Society
- Society for Mathematical Biology
- Society for Natural Sciences
- 2016 - Course Module Lead for FOOD2031 & FOOD5241M covering nutritional chemistry and food and drug biochemistry.
- 2016-2019 Contributor for Network and Systems Modelling for FOOD3130 Food Research: Recent Revelations and Disputes.
- 2019 - Contributor fo rRadical Reaction Mechanisms and Fatty Acid Oxdation for FOOD5196M Impacts of Processing on Nutritional Quality.
I welcome motivated Chemistry-focussed students wanting to explore bioinformatics and the use of biomarkers in molecular epidemiology. I welcome Natural Sciences students motivated by multi-disciplinary projects including medicinal or biological chemistry, computational molecular biochemistry, or metabolic state prediction in health and disease. I am also keen to host students with experience in computing and mathematics, especially formal methods for mathematical biology, biostatistics and interests in machine learning.
Every year, I host Summer vacation internships or have collaborators interested in sharing students. Enquire early in the New Year if you are interested in joining my research group for a scholarship-funded project during the Summer. There are a number of organisations and societies listed here and here that offer funding and scholarships.
Current and Former Research Students
- H Panesar, S Yuan & Y Wang (2021) Investigating network properties of bi-partite graphs that project QSAR and ADME for discriminating modes of action of compounds for long COVID syndrome.
- Y Jiang (2021) Functional analysis for coninuous glucose measurement time series.
- A Blick (2020-21) Analysis of individual dietary patterns and food intake and the misreporting when carrying out self-reported dietary assessments.
- J Wills (2020-21) Analysis of historical trends of child-stunting and crop yield in Kenya.
- I Blicknall & P Chalmers (2020-21) Analysis of de novo lipogenesis-associated TAG lipid abundances between organs.
- X Shen (2020) Polysaccharide organisation of marine biofilms, understanding the physicochemical constraints for the design of repellent surfaces for culinary use.
- S Wu (2020) Interactions of drugs on cysteine-rich kidney stones.
- P Zhang (2020) Assessing HbA1c measurements by Statistical modelling and clustering of blood pressure measurements.
- M Li (2020) Discussing uncertainties in OGTT and CGM in the third trimester of pregnancy.
- K Zhang (2020) with Nienyun Sharon Hsu and Yaowei Xun - Binding sites of oncogenic fusion proteins of non-small cell lung cancer.
- T Liu & CW Chan (2019-20) Statistical modelling and clustering of blood pressure measurements.
- O Taylor (2019-20) Re-assessment of unsupervised clustering of retrospective early gestational diabetes and OGTT clinical data.
- E Wong (2019-20) Computer-aided drug design of peptide inhibitor binding for targets in basal-like breast cancer.
- Y Jiang (2019-20) Computational Systems Biochemistry – Cyclic and feed-forward motif behaviour from flux patterns of anaplerotic metabolic reactions in E.coli.
- O Taylor (2019) Wellcome Trust-funded Summer Studentship: An unsupervised multivariate analysis of early gestational diabetes clinical biomarkers.
- Y Xun (2019) with Nienyun Sharon Hsu – Molecular docking of SHC domains to short linear motifs from intrinsically disordered regions in proteins related to intracellular signalling.
- J Shu (2019) with Yuwei Li – Microbial and metabolic modelling of repeated Stag Hunt competition in cyclic Rock-Paper-Scissor interactions.
- A Shen (2019) Systematic review of coagulation biomarkers on early gestational diabetes.
- T He (2019) Systematic review of the hepatic and trace element biomarkers on early gestational diabetes.
- Y Zhang (2019) Systematic review of the thyroid and anaemia biomarkers on early gestational diabetes.
- H Tong (2018-9) with Helen Chappell – Modelling interactions of aflatoxins and their metabolites with calcium phosphate,
- G Gornall (2018-9) with Helen Chappell – Water activity and hydration shells of polyphenols.
- S Holmes (2018-9) Rock-paper-scissor dynamics – Development of a cellular automaton model for interacting bacterial colonies.
- L Potts (2018-9) Identifying metabolic biomarker correlations in clinical data from early gestational diabetes.
- K Daly (2018) Erasmus+ Project Student from DIT Dublin, Ireland: Quantitative methods for exploring metabolomics:
i) Biostatistical methods for anthropometry landscape modelling according to dominant phospholipids in circulating lymphocytes.
ii) Unsupervised machine learning pattern recognition to characterise physiological biomarkers indicative of gestational diabetes in the first trimester.
- L Yeo (2018) Phase I metabolism prediction of xenobiotics – A comparison of mechanistic biotransformations by CYP2D6 and CYP2C9 predicted using SPORCalc.
- Y Li (2018) Identification of functional motifs from GAB1 intrinsically disordered regions and an assessment of their stabilising interactions with SHC binding domains.
- W Zhou (2018) Characterising PPI binding motifs in intrinsically disordered regions used by KIT protein signalling, for peptidomimetic drug target discovery in signalling protein aggregates in breast cancer.
- Z Ma (2017) Molecular recognition of isosterol and triterpenoid-based ligand-binding constraints to inform structure-based drug design.
- D Wu (2017) Identification of potential drug targets from hub-associated motifs from transcription factor networks, found in basal (triple-negative) breast cancer patients.
- H Tong (2017) University of Leeds and EPSRC-funded Summer Studentship: Canonical correlation analysis & combinatoric composition analysis of acyl abundance in phospholipids and neutral acylglycerol, derived from large scale lipidomics.
- M Liu (2017) Discrimination of Her2 and Luminal – A breast cancer patients revealed by hierarchical clustering of nuclear receptor expression patterns.
- W Pan (2017) Explicit solvent molecular modelling – Hydrogen-bonding networks determined from conformational sampling of MD-generated conformation ensembles (with AMBER) followed by geometry optimisation with DFT (with CASTEP).
- A Ackroyd (2016-7) with Alan Mackie – Time-dependent correlation clustering analysis to reveal coherence between self-reported satiety with physiological data collected from lateral MRI imaging and circulating blood biomarkers linked to gastric emptying.
- A Bawden (2016-7) 2D machine learning stratification of fat lipid biomarkers, useful for molecular epidemiology and fish-oil intervention studies.
- M Harland (2016-7) with David Hauton – Regressing cardiac QT and RR interval signals to both logarithmic and parabolic models to determine the accuracy of QTc interval changes during cardiovascular exercise and nitrate supplementation.
Research groups and institutes
- Food Chemistry and Biochemistry
- Obesity, Cancer and Metabolic Disease