Detalhe da pesquisa
1.
A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation.
Cell
; 178(1): 91-106.e23, 2019 06 27.
Artigo
em Inglês
| MEDLINE | ID: mdl-31178116
2.
Fast activation maximization for molecular sequence design.
BMC Bioinformatics
; 22(1): 510, 2021 Oct 20.
Artigo
em Inglês
| MEDLINE | ID: mdl-34670493
3.
CPA-Perturb-seq: Multiplexed single-cell characterization of alternative polyadenylation regulators.
bioRxiv
; 2023 Feb 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-36798324
4.
The anti-cancer compound JTE-607 reveals hidden sequence specificity of the mRNA 3' processing machinery.
bioRxiv
; 2023 Apr 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-37090613
5.
The anticancer compound JTE-607 reveals hidden sequence specificity of the mRNA 3' processing machinery.
Nat Struct Mol Biol
; 30(12): 1947-1957, 2023 Dec.
Artigo
em Inglês
| MEDLINE | ID: mdl-38087090
6.
Rewriting regulatory DNA to dissect and reprogram gene expression.
bioRxiv
; 2023 Dec 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-38187584
7.
Deciphering the impact of genetic variation on human polyadenylation using APARENT2.
Genome Biol
; 23(1): 232, 2022 11 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-36335397
8.
Interpreting Neural Networks for Biological Sequences by Learning Stochastic Masks.
Nat Mach Intell
; 4(1): 41-54, 2022 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-35966405
9.
A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences.
Cell Syst
; 11(1): 49-62.e16, 2020 07 22.
Artigo
em Inglês
| MEDLINE | ID: mdl-32711843