Chuan Lu BEng (Tianjin, China), MSc (Leuven, Belgium), PhD(Leuven)


Contact Details

Room Number..........:  E43
Building....................:  Llandinam
Phone.......................:   +44 (0)1970 628405
E-Mail........................:   cul
Home Page...............:   Personal

External Publication Websites:
Google Scholar

Research Groups

Teaching Areas

Modules Taught

  • CC18010: Datblygiad Proffesiynol a Phersonol
  • CC39440: Prosiect Hir
  • CS18010: Professional and Personal Development
  • CS31810: Computational Bioinformatics
  • CS36110: Machine Learning
  • CS39440: Major Project
  • CSM3120: Modelling, Managing and Securing Data
  • CSM6420: Machine Learning for Intelligent Systems
  • SEM6420: Machine Learning for Intelligent Systems


Corrigendum to Metabolomic-based biomarker discovery for non-invasive lung cancer screening: A case study [Biochimica et Biophysica Acta (BBA) – General subjects, vol. 1860 (2016), pp. 2682–2687]O'shea, K., Cameron, S. J., Lewis, K. E., Lewis, P. D., Lu, C. & Mur, L. A. 2017 In : Biochimica et Biophysica Acta (BBA) - General Subjects.
The morphological ultrasound types known as ‘blob’ and ‘bagel’ signs should be reclassified from probable to definite ectopic pregnancyNadim, B., Infante, F., Lu, C., Sathasivam, N. & Condous, G. 2017 In : Ultrasound in Obstetrics and Gynecology.
Association between three-dimensional transvaginal sonographic markers and outcome of pregnancy of unknown location: A pilot studyReid, S., Nadim, B., Bignardi, T., Lu, C., Martins, W. P. & Condous, G. 2016 In : Ultrasound in Obstetrics and Gynecology.48, 5, p. 650-6556 p.
Metabolomic-based biomarker discovery for non-invasive lung cancer screening: A case studyO'Shea, K., Cameron, S. J. S., Lewis, K. E., Lewis, P. D., Lu, C. & Mur, L. A. J. 2016 In : Biochimica et Biophysica Acta (BBA) - General Subjects.1860, 11 (Part B), p. 2682-26876 p.
Interpreting the real-time dynamic ‘sliding sign’ and predicting pouch of Douglas obliteration: an interobserver, intraobserver, diagnostic-accuracy and learning-curve studyMenakaya, U., Infante, F., Lu, C., Phua, C., Model, A., Messyne, F., Brainwood, M., Reid, S. & Condous, G. 2016 In : Ultrasound in Obstetrics and Gynecology.48, 1, p. 113-120
Is there a difference in the behaviour and subsequent management of ectopic pregnancies seen at first scan compared to those ectopic pregnancies which commence as pregnancies of unknown location?Lattouf, I., Lu, C., Pixton, S., Reid, S. & Condous, G. 2016 In : Australian and New Zealand Journal of Obstetrics and Gynaecology.56, 1, p. 107-1126 p.
Does the Transvaginal Ultrasound Uterine “Sliding Sign” Alone Outperform Direct Visualization Using Sonovaginography for the Prediction of Rectal/Rectosigmoid Deep Infiltrating Endometriosis?Reid, S., Lu, C., Gerges, B. & Condous, G. 2016 p. S108-S109
The prediction of pouch of Douglas obliteration using offline analysis of the transvaginal ultrasound ‘sliding sign’ technique: inter- and intra-observer reproducibilityReid, S., Lu, C., Casikar, I., Mein, B., Magotti, R., Ludlow, J., Benzie, R. & Condous, G. 2015 In : Acta Obstetricia et Gynecologica Scandinavica.94, 12, p. 1237-1246
Office gel sonovaginography for the prediction of posterior deep infiltrating endometriosis: a multicenter prospective observational studyReid, S., Lu, C., Hardy, N., Casikar, I., Reid, G., Cario, G., Chou, D., Almashat, D. & Condous, G. 2014 In : Ultrasound in Obstetrics and Gynecology.44, 6, p. 710-7189 p.
An investigation into eukaryotic pseudouridine synthasesKing, R. D. & Lu, C. 2014 In : Journal of Bioinformatics and Computational Biology.12, 4, 16 p.
Is there a correlation between aberrant embryonic crown-rump length growth velocities and subsequent birth weightsMongelli, M., Lu, C., Reid, S., Stamatopoulos, N., Sankaralingam, K., Casikar, I., Hardy, N. W. & Condous, G. 2013 In : Ultrasound in Obstetrics and Gynecology.42, s1, p. 13-131 p.
On the formalization and reuse of scientific researchKing, R. D., Liakata, M., Lu, C., Oliver, S. G. & Soldatova, L. N. 2011 In : Interface.8, 63, p. 1440-14489 p.
Management of women referred to an acute gynecology unit: impact of an ultrasound-based model of care.Bignardi, T., Burnet, S., Alhamdan, D., Lu, C., Pardey, J., Benzie, R. & Condous, G. 2011 In : Ultrasound in Obstetrics and Gynecology.35, 3, p. 344-3485 p.
Further developments towards a genome-scale metabolic model of yeastDobson, P. D., Smallbone, K., Jameson, D., Simeonidis, E., Lanthaler, K., Pir, P., Lu, C., Swainston, N., Dunn, W. B., Fisher, P., Hull, D., Brown, M., Oshota, O., Stanford, N. J., Kell, D. B., King, R. D., Oliver, S. G., Stevens, R. D. & Mendes, P. 2010 In : BMC Systems Biology.4, 145
Constraint-based optimisation tools for semi-automated refinement of genome-scale yeast metabolic modelsPir, P., Dobson, P. D., Smallbone, K., Mendes, P., King, R. D., Lu, C., Oliver, S. G. & Clare, A. 2010
The metabolic transition during disease following infection of Arabidopsis thaliana by Pseudomonas syringae pv. tomato.Ward, J. L., Forcat, S., Beckmann, M., Bennett, M., Miller, S. J., Baker, J. M., Hawkins, N. D., Vermeer, C. P., Lu, C., Lin, W., Truman, W. M., Beale, M. H., Draper, J., Mansfield, J. W. & Grant, M. 2010 In : Plant Journal.63, 3, p. 443-45715 p.
Report on structural comparison and validation of the genome scale metabolic models for Saccharomyces cerevisiaeLu, C., Whelan, K. E. & King, R. D. 2010 European Commission. 16 p.
Automatic identification and restoration of reaction gaps in the consensus reconstruction network for yeast metabolismLu, C. & King, R. D. 2010 p. 1-7171 p.
An investigation into the population abundance distribution of mRNAs, proteins, and metabolites in biological systemsLu, C. & King, R. D. 2009 In : Bioinformatics.25, 16, p. 2020-20278 p.
Prospective internal validation of mathematical models to predict malignancy in adnexal masses: results from the International Ovarian Tumor Analysis (IOTA) StudyVan Holsbeke, C., Van Calster, B., Testa, A. C., Domali, E., Lu, C., Van Huffel, S., Valentin, L. & Timmerman, D. 2009 In : Clinical Cancer Research.15, 684, p. 684-6918 p.
Bagging linear sparse Bayesian learning models for variable selection in cancer diagnosisDevos, A., Van Huffel, S., Lu, C., Suykens, J. A. K. & Arus, C. 2007 In : IEEE Transactions on Information Technology in Biomedicine.11, 3, p. 338-34710 p.
Preoperative diagnosis of ovarian tumors using Bayesian kernel-based methodsVan Calster, B., Timmerman, D., Lu, C., Suykens, J. A. K., Valentin, L., Van Holsbeke, C., Amant, F., Vergote, I. & Van Huffel, S. 2007 In : Ultrasound in Obstetrics and Gynecology.29, 5, p. 496-5049 p.