A carregar...

In silico learning of tumor evolution through mutational time series

Cancer arises through the accumulation of somatic mutations over time. Understanding the sequence of mutation occurrence during cancer progression can assist early and accurate diagnosis and improve clinical decision-making. Here we employ long short-term memory (LSTM) networks, a class of recurrent...

ver descrição completa

Na minha lista:
Detalhes bibliográficos
Publicado no:Proc Natl Acad Sci U S A
Main Authors: Auslander, Noam, Wolf, Yuri I., Koonin, Eugene V.
Formato: Artigo
Idioma:Inglês
Publicado em: National Academy of Sciences 2019
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6510994/
https://ncbi.nlm.nih.gov/pubmed/31015295
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1901695116
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!