K., Lee, J. T., Rasanen, K., Weinstein, G. S. and Herlyn, M. (2011). Detecting

targeting mesenchymal-like subpopulations within squamous cell carcinomas,

l Cycle, 10, pp. 2008–2016.

F., Crimmins, B. S., Hopke, P. K. and Holsen, T. M. (2016). Comprehensive

erging chemical discovery: novel polyfluorinated compounds in lake Michigan

ut, Environmental Science & Technology, 50, pp. 9460–9468.

and Jones, P. A. (2011). A decade of exploring the cancer epigenome —

logical and translational implications. Nature Reviews Cancer, 11, pp. 726–734.

Shaket, L., Anzai, I. A., Adesena, O. and Barstow, B. (2016). Rapid

struction of a whole-genome transposon insertion collection for Shewanella

idensis by Knockout Sudoku, Nature Communications, 7, pp. 13270.

A. (2017). Predicting enhancer activity and variant impact using gkm-SVM,

man Mutation, 38, pp. 1251–1258.

and Tarpey, P. S. (2013). What is next generation sequencing? Archives of

ease in Childhood – Education and Practice, 98, pp. 236–238.

Stokes, A. M. and Quarles, C. C. (2020). Analysis of postprocessing steps for

due function dependent dynamic susceptibility contrast (DSC)-MRI

markers and their clinical impact on glioma grading for both 1.5 and

Journal of Magnetic Resonance Imaging, 51, pp. 547–553.

LeCun, Y. and Hinton, G. (2015). Deep learning, Nature, 521, pp. 436–444.

(1980). The computer as a physical system: a microscopic quantum mechanical

miltonian model of computers as represented by Turing machines, Journal of

istical Physics, 22, pp. 563–591.

Y. and Yekutieli, D. (2001). The control of the false discovery rate in multiple

ing under dependency, The Annuals of Statistics, 29, pp. 1165–1188.

Pastell, M., Bonora, F., Tassinari, P. and Torreggiani, D. (2020). A generalised

itive model to characterise dairy cows' responses to heat stress, Animal, 14, pp.

–424.

A., Cohen, M. A. and Gonnet, G. H. (1994). Amino acid substitution during

ctionally constrained divergent evolution of protein sequences, Protein

gineering, 7, pp. 1323–1332.

A., Dalby, A. R. and Yang, Z. R. (2004). Reduced bio basis function neural

work for identification of protein phosphorylation sites: comparison with pattern

ognition algorithms, Computational Biology and Chemistry, 28, pp. 75–85.

er, E. (2001). Multiscale Gaussian random fields and their application to

mological simulations, The Astrophysical Journal, 137, pp. 1–20.

a, M., Kirillov, E., Shi, W., Bugrim, A., Nikolsky, Y. and Nikolskaya, T. (2010).

modal gene expression patterns in breast cancer, BMC Genomics, 11, pp. S8.

Ancona, D., Davila-Ortiz, G., Chel-Guerrero, L. A. and Torruco-Uco, J. G.

18). ACE-I inhibitory activity from Phaseolus lunatus and Phaseolus vulgaris

tide fractions obtained by ultrafiltration, Journal of Medical Food, 18, pp.

7–1254.