Zobrazeno 1 - 10
of 208
pro vyhledávání: '"MacArthur, Ben D."'
Autor:
Baptista, Anthony, Barp, Alessandro, Chakraborti, Tapabrata, Harbron, Chris, MacArthur, Ben D., Banerji, Christopher R. S.
Deep neural networks (DNNs) are powerful tools for approximating the distribution of complex data. It is known that data passing through a trained DNN classifier undergoes a series of geometric and topological simplifications. While some progress has
Externí odkaz:
http://arxiv.org/abs/2404.14265
Autor:
Mitra, Robin, McGough, Sarah F., Chakraborti, Tapabrata, Holmes, Chris, Copping, Ryan, Hagenbuch, Niels, Biedermann, Stefanie, Noonan, Jack, Lehmann, Brieuc, Shenvi, Aditi, Doan, Xuan Vinh, Leslie, David, Bianconi, Ginestra, Sanchez-Garcia, Ruben, Davies, Alisha, Mackintosh, Maxine, Andrinopoulou, Eleni-Rosalina, Basiri, Anahid, Harbron, Chris, MacArthur, Ben D.
Missing data are an unavoidable complication in many machine learning tasks. When data are `missing at random' there exist a range of tools and techniques to deal with the issue. However, as machine learning studies become more ambitious, and seek to
Externí odkaz:
http://arxiv.org/abs/2304.01429
Publikováno v:
Theory in Biosciences (2021)
Complex systems of intracellular biochemical reactions have a central role in regulating cell identities and functions. Biochemical reaction systems are typically studied using the language and tools of graph theory. However, graph representations on
Externí odkaz:
http://arxiv.org/abs/2010.01049
Akademický článek
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Populations of mammalian stem cells commonly exhibit considerable cell-cell variability. However, the functional role of this diversity is unclear. Here, we analyze expression fluctuations of the stem cell surface marker Sca1 in mouse hematopoietic p
Externí odkaz:
http://arxiv.org/abs/1504.07266
Autor:
Smyth, Conor, Špakulova, Iva, Cotton-Barratt, Owen, Rafiq, Sajjad, Tapper, William, Upstill-Goddard, Rosanna, Hopper, John L., Makalic, Enes, Schmidt, Daniel F., Kapuscinski, Miroslav, Fliege, Jörg, Collins, Andrew, Brodzki, Jacek, Eccles, Diana M., MacArthur, Ben D.
Many common diseases have a complex genetic basis in which large numbers of genetic variations combine with environmental and lifestyle factors to determine risk. However, quantifying such polygenic effects and their relationship to disease risk has
Externí odkaz:
http://arxiv.org/abs/1406.3828
Publikováno v:
Phys. Rev. Lett. 104, 168701 (2010)
We present a model of adaptive regulatory networks consisting of a simple biologically-motivated rewiring procedure coupled to an elementary stability criterion. The resulting networks exhibit a characteristic stationary heavy-tailed degree distribut
Externí odkaz:
http://arxiv.org/abs/0912.2008
Publikováno v:
Phys. Rev. E 80, 026117 (2009)
Many real-world complex networks contain a significant amount of structural redundancy, in which multiple vertices play identical topological roles. Such redundancy arises naturally from the simple growth processes which form and shape many real-worl
Externí odkaz:
http://arxiv.org/abs/0904.3192
Akademický článek
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Publikováno v:
Physical Review E, Vol 78,Page: 046102, 2008
A defining feature of many large empirical networks is their intrinsic complexity. However, many networks also contain a large degree of structural repetition. An immediate question then arises: can we characterize essential network complexity while
Externí odkaz:
http://arxiv.org/abs/0802.4318