Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

Autor: Mourikis, TP, Benedetti, L, Foxall, E, Temelkovski, D, Nulsen, J, Perner, J, Cereda, M, Lagergren, J, Howell, M, Yau, C, Fitzgerald, RC, Scaffidi, P, Noorani, A, Edwards, PAW, Elliott, RF, Grehan, N, Nutzinger, B, Hughes, C, Fidziukiewicz, E, Bornschein, J, MacRae, S, Crawte, J, Northrop, A, Contino, G, Li, X, De la Rue, R, Katz-Summercorn, A, Abbas, S, Loureda, D, O'Donovan, M, Miremadi, A, Malhotra, S, Tripathi, M, Tavare, S, Lynch, AG, Eldridge, M, Secrier, M, Bower, L, Devonshire, G, Jammula, S, Davies, J, Crichton, C, Carroll, N, Safranek, P, Hindmarsh, A, Sujendran, V, Hayes, SJ, Ang, Y, Sharrocks, A, Preston, SR, Oakes, S, Bagwan, I, Save, V, Skipworth, RJE, Hupp, TR, O'Neill, JR, Tucker, O, Beggs, A, Taniere, P, Puig, S, Underwood, TJ, Walker, RC, Grace, BL, Barr, H, Shepherd, N, Old, O, Gossage, J, Davies, A, Chang, F, Zylstra, J, Mahadeva, U, Goh, V, Sanders, G, Berrisford, R, Harden, C, Lewis, M, Cheong, E, Kumar, B, Parsons, SL, Soomro, I, Kaye, P, Saunders, J, Lovat, L, Haidry, R, Igali, L, Scott, M, Sothi, S, Suortamo, S, Lishman, S, Hanna, GB, Peters, CJ, Moorthy, K, Grabowska, A, Turkington, R, McManus, D, Khoo, D, Fickling, W, Ciccarelli, FD

The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::56bbcb4834a826025994807c5a97eb9d
https://www.repository.cam.ac.uk/handle/1810/307928

An in silico analytical study of lung cancer and smokers datasets from gene expression omnibus (GEO) for prediction of differentially expressed genes

Autor: Grace Bl, Ahmad Mw, Madar Ih, Atif N. Hasan, Tarique N. Hasan

Publikováno v: Bioinformation

Smoking is the leading cause of lung cancer development and several genes have been identified as potential biomarker for lungs cancer. Contributing to the present scientific knowledge of biomarkers for lung cancer two different data sets, i.e. GDS32

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eaadd5ae6b5ae08a96331e2311472a7b
https://doi.org/10.6026/97320630011229

Machine learning to predict early recurrence after oesophageal cancer surgery.

Autor: Rahman SA; Cancer Sciences Unit, University of Southampton, Southampton, UK., Walker RC; Cancer Sciences Unit, University of Southampton, Southampton, UK., Lloyd MA; Cancer Sciences Unit, University of Southampton, Southampton, UK., Grace BL; Cancer Sciences Unit, University of Southampton, Southampton, UK., van Boxel GI; Department of Surgery, University Medical Centre, Utrecht, the Netherlands., Kingma BF; Department of Surgery, University Medical Centre, Utrecht, the Netherlands., Ruurda JP; Department of Surgery, University Medical Centre, Utrecht, the Netherlands., van Hillegersberg R; Department of Surgery, University Medical Centre, Utrecht, the Netherlands., Harris S; Department of Public Health Sciences and Medical Statistics, University of Southampton, Southampton, UK., Parsons S; Department of Surgery, Nottingham University Hospitals NHS Trust, Nottingham, UK., Mercer S; Department of Surgery, Portsmouth Hospitals NHS Trust, Portsmouth, UK., Griffiths EA; Department of Upper Gastrointestinal Surgery, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK., O'Neill JR; Cambridge Oesophagogastric Centre, Addenbrookes Hospital, Cambridge University Hospitals Foundation Trust, Cambridge, UK., Turkington R; Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, UK., Fitzgerald RC; Hutchison/Medical Research Council Cancer Unit, University of Cambridge, Cambridge, UK., Underwood TJ; Cancer Sciences Unit, University of Southampton, Southampton, UK.

Publikováno v: The British journal of surgery [Br J Surg] 2020 Jul; Vol. 107 (8), pp. 1042-1052. Date of Electronic Publication: 2020 Jan 30.

The Violence of Uncertainty - Undermining Immigrant and Refugee Health.

Autor: Grace BL; From the Colleges of Social Work (B.G., B.R.) and Medicine (R.B.), University of South Carolina, Columbia., Bais R; From the Colleges of Social Work (B.G., B.R.) and Medicine (R.B.), University of South Carolina, Columbia., Roth BJ; From the Colleges of Social Work (B.G., B.R.) and Medicine (R.B.), University of South Carolina, Columbia.

Publikováno v: The New England journal of medicine [N Engl J Med] 2018 Sep 06; Vol. 379 (10), pp. 904-905.

An in silico analytical study of lung cancer and smokers datasets from gene expression omnibus (GEO) for prediction of differentially expressed genes.

Autor: Hasan AN; Dept. of Bioinformatics, Jamia Millia Islamia, New Delhi, India ; Division of Bioinformatics, Noor-Amna Foundation for Research and Education, Bettiah, Bihar, India., Ahmad MW; Dept. of Software Engg, College of Computer Science, King Saud University, Riyadh, Saudi Arabia., Madar IH; Dept. of Biotechnology and Bioinformatics, Bishop Heber College, Tiruchirappalli, TN, India., Grace BL; Dept of Biotechnology, Vinayaka Missions University, Salem, TN, India., Hasan TN; Division of Bioinformatics, Noor-Amna Foundation for Research and Education, Bettiah, Bihar, India ; R & D Center, Bharathiar University, Coimbatore-641046, TN,India.

Publikováno v: Bioinformation [Bioinformation] 2015 May 28; Vol. 11 (5), pp. 229-35. Date of Electronic Publication: 2015 May 28 (Print Publication: 2015).