Detalhe da pesquisa
1.
Recording of elapsed time and temporal information about biological events using Cas9.
Cell
; 184(4): 1047-1063.e23, 2021 02 18.
Artigo
em Inglês
| MEDLINE | ID: mdl-33539780
2.
Massively parallel evaluation and computational prediction of the activities and specificities of 17 small Cas9s.
Nat Methods
; 20(7): 999-1009, 2023 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-37188955
3.
Sniper2L is a high-fidelity Cas9 variant with high activity.
Nat Chem Biol
; 19(8): 972-980, 2023 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-36894722
4.
TargetNet: functional microRNA target prediction with deep neural networks.
Bioinformatics
; 38(3): 671-677, 2022 01 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-34677573
5.
Deep learning in bioinformatics.
Brief Bioinform
; 18(5): 851-869, 2017 09 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-27473064
6.
Deep learning models to predict the editing efficiencies and outcomes of diverse base editors.
Nat Biotechnol
; 42(3): 484-497, 2024 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-37188916
7.
Improving generalization performance of electrocardiogram classification models.
Physiol Meas
; 44(5)2023 05 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-36638544
8.
DNA Privacy: Analyzing Malicious DNA Sequences Using Deep Neural Networks.
IEEE/ACM Trans Comput Biol Bioinform
; 19(2): 888-898, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-32809941
9.
Protein transfer learning improves identification of heat shock protein families.
PLoS One
; 16(5): e0251865, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-34003870
10.
Predicting the efficiency of prime editing guide RNAs in human cells.
Nat Biotechnol
; 39(2): 198-206, 2021 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-32958957
11.
Generation of a more efficient prime editor 2 by addition of the Rad51 DNA-binding domain.
Nat Commun
; 12(1): 5617, 2021 09 23.
Artigo
em Inglês
| MEDLINE | ID: mdl-34556671
12.
Learned Embeddings from Deep Learning to Visualize and Predict Protein Sets.
Curr Protoc
; 1(5): e113, 2021 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-33961736
13.
Prediction of the sequence-specific cleavage activity of Cas9 variants.
Nat Biotechnol
; 38(11): 1328-1336, 2020 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-32514125
14.
High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells.
Nat Biomed Eng
; 4(1): 111-124, 2020 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-31937939
15.
Sequence-specific prediction of the efficiencies of adenine and cytosine base editors.
Nat Biotechnol
; 38(9): 1037-1043, 2020 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-32632303
16.
Author Correction: Predicting the efficiency of prime editing guide RNAs in human cells.
Nat Biotechnol
; 42(3): 529, 2024 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-38332117
17.
SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with high generalization performance.
Sci Adv
; 5(11): eaax9249, 2019 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-31723604
18.
Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.
Nat Biotechnol
; 36(3): 239-241, 2018 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-29431740