Items where Author is "Lancashire, L"

LANCASHIRE, L. and BALL, G., 2010. Computational and statistical methodologies for data mining in bioinformatics. In: T. ATHANASIOU, H. DEBAS and A. DARZI, eds., Key topics in surgical research and methodology. Wiley, pp. 337-350. ISBN 9780470681992

LANCASHIRE, L., LEMETRE, C. and BALL, G., 2009. An introduction to artificial neural networks in bioinformatics - application to complex microarray and mass spectrometry datasets in cancer studies. Briefings in Bioinformatics, 10 (3), pp. 315-329. ISSN 1477-4054

BOATENG, J., KAY, R., LANCASHIRE, L., BROWN, P., VELLOSO, C., BOULOUX, P., TEALE, P., ROBERTS, J., REES, R., BALL, G., HARRIDGE, S., GOLDSPINK, G. and CREASER, C., 2009. A proteomic approach combining mass spectrometric and bioinformatics analysis for the detection and identification of biomarkers of administration of exogenous human growth hormone in humans. Proteomics - Clinical Applications, 3 (8), pp. 912-922. ISSN 1862-8346

MATHAROO-BALL, B., HUGHES, C., LANCASHIRE, L., TOOTH, D., BALL, G., CREASER, C., ELGASIM, M., REES, R., LAYFIELD, R. and ATIOMO, W., 2007. Characterization of biomarkers in polycystic ovary syndrome (PCOS) using multiple distinct proteomic platforms. Journal of Proteome Research, 6 (8), pp. 3321-3328. ISSN 1535-3893

MATHAROO-BALL, B., HUGHES, C., LANCASHIRE, L., TOOTH, D., BALL, G., CREASER, C., ELGASIM, M., REES, R.C., LAYFIELD, R. and ATIOMO, W., 2007. Combinational proteomic characterization of biomarkers in polycystic ovary syndrome (PCOS). Journal of Proteome Research, 6 (8), pp. 3321-3328.

MATHAROO-BALL, B., RATCLIFFE, L., LANCASHIRE, L., UGUREL, S., MILES, A.K., WESTON, D.J., REES, R., SCHADENDORF, D., BALL, G. and CREASER, C.S., 2007. Diagnostic biomarkers differentiating metastatic melanoma patients from healthy controls identified by an integrated MALDI-TOF mass spectrometry/bioinformatic approach. Proteomics Clinical Applications, 1 (6), pp. 605-620. ISSN 1862-8346

BALLS, G., QUATAN, N., MICHAEL, A., LANCASHIRE, L., ADAMS, V., HOFFMAN, B., PFIRSCHKE, C., RUSSELL, N., WHELAN, M. and PANDHA, H., 2007. Immunological response patterns correlate with clinical outcome after allogeneic vaccination in hormone resistant prostate cancer metastatic to bone. Journal of Immunotherapy, 30 (8), p. 891. ISSN 1524-9557

IVERSEN, C., LANCASHIRE, L., WADDINGTON, M., FORSYTHE, S. and BALL, G., 2006. Identification of Enterobacter sakazakii from closely related species: the use of artificial neural networks in the analysis of biochemical and 16S rDNA data. BMC Microbiology, 6: 28. ISSN 1471-2180

BOATENG, J., LANCASHIRE, L., BROWN, P., AHMAD, M., MATHAROO-BALL, B., DAVY, R., YANG, S.Y., ROBERTS, J., TEALE, P., VELLOSO, C., REES, R., BALL, G., GOLDSPINK, G. and CREASER, C., 2006. The use of proteomic and bioinformatics techniques for the detection of protein biomarkers following growth hormone administration. The Internet Journal of Genomics and Proteomics, 2 (2). ISSN 1540-2630

LANCASHIRE, L., SCHMID, O., SHAH, H. and BALL, G., 2005. Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis. Bioinformatics, 21 (10), pp. 2191-2199. ISSN 1367-4803

SCHMID, O., BALL, G., LANCASHIRE, L., CULAK, R. and SHAH, H., 2005. New approaches to identification of bacterial pathogens by surface enhanced laser desorption/ionization time of flight mass spectrometry in concert with artificial neural networks, with special reference to Neisseria gonorrhoeae. Journal of Medical Microbiology, 54 (12), pp. 1205-1211. ISSN 0022-2615

MIAN, S., UGUREL, S., PARKINSON, E., SCHLENZKA, I., DRYDEN, I., LANCASHIRE, L., BALL, G., CREASER, C., REES, R. and SCHADENDORF, D., 2005. Serum proteomic fingerprinting discriminates between clinical stages and predicts disease progression in melanoma patients. Journal of Clinical Oncology, 23 (22), pp. 5088-5093. ISSN 0732-183X

LANCASHIRE, L., UGUREL, S., CREASER, C., SCHADENDORF, D., REES, R. and BALL, G., 2005. Utilizing artificial neural networks to elucidate serum biomarker patterns which discriminate between clinical stages in melanoma. Proceedings of the 2005 Ieee Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp. 455-460.