Daniel Temko
Queen Mary University of London
16 Papers
14 Citations
Daniel Temko is an academic researcher from Queen Mary University of London. The author has contributed to research in topics: Cancer & Mutation. The author has an hindex of 6, co-authored 10 publications. Previous affiliations of Daniel Temko include University College London.
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Papers
The effects of mutational processes and selection on driver mutations across cancer types
Daniel Temko,Daniel Temko,Ian Tomlinson,Simone Severini,Simone Severini,Benjamin Schuster-Böckler,Trevor A. Graham +6 more
TL;DR: Public sequencing data is used to infer the effect of mutation and selection on a set of driver mutations and suggest that selection frequently dominates, showing that while mutational processes have a large role in determining which driver mutations are present in a cancer, the role of selection frequently dominated.
Measuring single cell divisions in human tissues from multi-region sequencing data.
Benjamin Werner,Benjamin Werner,Jack Case,Jack Case,Marc J Williams,Marc J Williams,Ketevan Chkhaidze,Daniel Temko,Javier Fernández-Mateos,George D. Cresswell,Daniel Nichol,William Cross,Inmaculada Spiteri,Weini Huang,Weini Huang,Ian Tomlinson,Chris P. Barnes,Trevor A. Graham,Andrea Sottoriva +18 more
TL;DR: It is shown that multi-sample genomic data from a single time point of normal and cancer tissues contains information on single-cell divisions, which allows inferring the mutation rate and the cell survival/death rate per division.
Spatial intra-tumor heterogeneity is associated with survival of lung adenocarcinoma patients
Hua-Jun Wu,Daniel Temko,Zoltan Maliga,Andre L. Moreira,Emi Sei,Darlan Conterno Minussi,Jamie Dean,Charlotte E. Lee,Qiong-Li Xu,Guillaume Hochart,Connor A. Jacobson,Clarence Yapp,Denis Schapiro,Peter K. Sorger,Erin H. Seeley,Nicholas Navin,Robert J. Downey,Franziska Michor +17 more
TL;DR: In this article , the authors presented a comprehensive spatial mapping of intra-tumor heterogeneity in lung adenocarcinoma and provided insights into the mechanisms and clinical consequences of GD.
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The effects of mutational process and selection on driver mutations across cancer types
TL;DR: Ass associations between a range of mutational processes, including those linked to smoking, ageing, APOBEC and DNA mismatch repair (MMR) and the presence of key driver mutations across cancer types are detected.
Mathematical Modeling Links Pregnancy-Associated Changes and Breast Cancer Risk
TL;DR: This work uses a simple mathematical model to show that recent data on the variation in numbers of breast epithelial cells with progenitor features due to pregnancy are sufficient to explain the known protective effect of full-term pregnancy in early adulthood for estrogen receptor-positive (ER+) breast cancer later in life.
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