Utilizing Artificial Neural Networks to Elucidate Serum Biomarker Patterns Which Discriminate Between Clinical Stages in Melanoma. - Lee Lancashire; Selma Ugurel; Colin Creaser; Dirk Schadendorf; Robert C. Rees; Graham R. Ball (CIBCB, 2005)

Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis. - Lee Lancashire; Oliver Schmid; Haroun Shah; Graham R. Ball (Bioinform., 2005)

Identification of gene transcript signatures predictive for estrogen receptor and lymph node status using a stepwise forward selection artificial neural network modelling approach. - Lee Lancashire; Robert C. Rees; Graham R. Ball (Artif. Intell. Medicine, 2008)

Artificial Neural Network Based Algorithm for Biomolecular Interactions Modeling. - Christophe Lemetre; Lee Lancashire; Robert C. Rees; Graham R. Ball (IWANN (1), 2009)

An introduction to artificial neural networks in bioinformatics - application to complex microarray and mass spectrometry datasets in cancer studies. - Lee Lancashire; Christophe Lemetre; Graham R. Ball (Briefings Bioinform., 2009)

PTSD Biomarker Database: deep dive metadatabase for PTSD biomarkers, visualizations and analysis tools. - Daniel Domingo-Fernández; Allison Provost; Alpha Tom Kodamullil; Josep Marín-Llaó; Heather Lasseter; Kristophe Diaz; Nikolaos P. Daskalakis; Lee Lancashire; Martin Hofmann-Apitius; Magali Haas (Database J. Biol. Databases Curation, 2019)

BRAINCommons: A Research Infrastructure Designed for Accelerated Discovery in Support of Brain Health. - Maryan Zirkle; Kimon Kotronis; Lee Lancashire; Eugene Rakhmatulin; Magali Haas (AMIA, 2022)

Deep Learning for Daily Monitoring of Parkinson's Disease Outside the Clinic Using Wearable Sensors. - Roozbeh Atri; Kevin Urban; Barbara Marebwa; Tanya Simuni; Caroline Tanner; Andrew Siderowf; Mark Frasier; Magali Haas; Lee Lancashire (Sensors, 2022)