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Lee Lancashire
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2020 – today
- 2022
- [j5]Roozbeh Atri
, Kevin Urban
, Barbara Marebwa
, Tanya Simuni, Caroline Tanner, Andrew Siderowf, Mark Frasier
, Magali Haas, Lee Lancashire
:
Deep Learning for Daily Monitoring of Parkinson's Disease Outside the Clinic Using Wearable Sensors. Sensors 22(18): 6831 (2022) - [c3]Maryan Zirkle, Kimon Kotronis, Lee Lancashire, Eugene Rakhmatulin, Magali Haas:
BRAINCommons: A Research Infrastructure Designed for Accelerated Discovery in Support of Brain Health. AMIA 2022
2010 – 2019
- 2019
- [j4]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:
PTSD Biomarker Database: deep dive metadatabase for PTSD biomarkers, visualizations and analysis tools. Database J. Biol. Databases Curation 2019: baz081 (2019)
2000 – 2009
- 2009
- [j3]Lee Lancashire
, Christophe Lemetre, Graham R. Ball
:
An introduction to artificial neural networks in bioinformatics - application to complex microarray and mass spectrometry datasets in cancer studies. Briefings Bioinform. 10(3): 315-329 (2009) - [c2]Christophe Lemetre, Lee Lancashire
, Robert C. Rees, Graham R. Ball
:
Artificial Neural Network Based Algorithm for Biomolecular Interactions Modeling. IWANN (1) 2009: 877-885 - 2008
- [j2]Lee Lancashire
, Robert C. Rees, Graham R. Ball
:
Identification of gene transcript signatures predictive for estrogen receptor and lymph node status using a stepwise forward selection artificial neural network modelling approach. Artif. Intell. Medicine 43(2): 99-111 (2008) - 2005
- [j1]Lee Lancashire
, Oliver Schmid, Haroun Shah, Graham R. Ball
:
Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis. Bioinform. 21(10): 2191-2199 (2005) - [c1]Lee Lancashire, Selma Ugurel, Colin Creaser, Dirk Schadendorf, Robert C. Rees, Graham R. Ball:
Utilizing Artificial Neural Networks to Elucidate Serum Biomarker Patterns Which Discriminate Between Clinical Stages in Melanoma. CIBCB 2005: 455-460
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