365 related articles for article (PubMed ID: 35241840)
1. Identification of antimicrobial peptides from the human gut microbiome using deep learning.
Ma Y; Guo Z; Xia B; Zhang Y; Liu X; Yu Y; Tang N; Tong X; Wang M; Ye X; Feng J; Chen Y; Wang J
Nat Biotechnol; 2022 Jun; 40(6):921-931. PubMed ID: 35241840
[TBL] [Abstract][Full Text] [Related]
2. Designing antimicrobial peptides using deep learning and molecular dynamic simulations.
Cao Q; Ge C; Wang X; Harvey PJ; Zhang Z; Ma Y; Wang X; Jia X; Mobli M; Craik DJ; Jiang T; Yang J; Wei Z; Wang Y; Chang S; Yu R
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36857616
[TBL] [Abstract][Full Text] [Related]
3. AMP-BERT: Prediction of antimicrobial peptide function based on a BERT model.
Lee H; Lee S; Lee I; Nam H
Protein Sci; 2023 Jan; 32(1):e4529. PubMed ID: 36461699
[TBL] [Abstract][Full Text] [Related]
4. An Intestinal Bacillus velezensis Isolate Displays Broad-Spectrum Antibacterial Activity and Prevents Infection of Both Gram-Positive and Gram-Negative Pathogens
Byun H; Brockett MR; Pu Q; Hrycko AJ; Beld J; Zhu J
J Bacteriol; 2023 Jun; 205(6):e0013323. PubMed ID: 37195186
[TBL] [Abstract][Full Text] [Related]
5. iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities.
Xu J; Li F; Li C; Guo X; Landersdorfer C; Shen HH; Peleg AY; Li J; Imoto S; Yao J; Akutsu T; Song J
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37369638
[TBL] [Abstract][Full Text] [Related]
6. AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens.
Li C; Sutherland D; Hammond SA; Yang C; Taho F; Bergman L; Houston S; Warren RL; Wong T; Hoang LMN; Cameron CE; Helbing CC; Birol I
BMC Genomics; 2022 Jan; 23(1):77. PubMed ID: 35078402
[TBL] [Abstract][Full Text] [Related]
7. A deep learning method for predicting the minimum inhibitory concentration of antimicrobial peptides against
Yan J; Zhang B; Zhou M; Campbell-Valois FX; Siu SWI
mSystems; 2023 Aug; 8(4):e0034523. PubMed ID: 37431995
[TBL] [Abstract][Full Text] [Related]
8. Discovery of novel antimicrobial peptides: A transcriptomic study of the sea anemone Cnidopus japonicus.
Grafskaia EN; Polina NF; Babenko VV; Kharlampieva DD; Bobrovsky PA; Manuvera VA; Farafonova TE; Anikanov NA; Lazarev VN
J Bioinform Comput Biol; 2018 Apr; 16(2):1840006. PubMed ID: 29361893
[TBL] [Abstract][Full Text] [Related]
9. Deep-ABPpred: identifying antibacterial peptides in protein sequences using bidirectional LSTM with word2vec.
Sharma R; Shrivastava S; Kumar Singh S; Kumar A; Saxena S; Kumar Singh R
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33784381
[TBL] [Abstract][Full Text] [Related]
10. iAMP-Attenpred: a novel antimicrobial peptide predictor based on BERT feature extraction method and CNN-BiLSTM-Attention combination model.
Xing W; Zhang J; Li C; Huo Y; Dong G
Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38055840
[TBL] [Abstract][Full Text] [Related]
11. Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides.
Pandi A; Adam D; Zare A; Trinh VT; Schaefer SL; Burt M; Klabunde B; Bobkova E; Kushwaha M; Foroughijabbari Y; Braun P; Spahn C; Preußer C; Pogge von Strandmann E; Bode HB; von Buttlar H; Bertrams W; Jung AL; Abendroth F; Schmeck B; Hummer G; Vázquez O; Erb TJ
Nat Commun; 2023 Nov; 14(1):7197. PubMed ID: 37938588
[TBL] [Abstract][Full Text] [Related]
12. The
Grafskaia E; Pavlova E; Babenko VV; Latsis I; Malakhova M; Lavrenova V; Bashkirov P; Belousov D; Klinov D; Lazarev V
Int J Mol Sci; 2020 Sep; 21(19):. PubMed ID: 32992666
[TBL] [Abstract][Full Text] [Related]
13. Antimicrobial Peptides from Human Microbiome Against Multidrug Efflux Pump of Pseudomonas aeruginosa: a Computational Study.
Mulpuru V; Mishra N
Probiotics Antimicrob Proteins; 2022 Feb; 14(1):180-188. PubMed ID: 35040024
[TBL] [Abstract][Full Text] [Related]
14. Discovery of antimicrobial peptides in the global microbiome with machine learning.
Santos-Júnior CD; Torres MDT; Duan Y; Rodríguez Del Río Á; Schmidt TSB; Chong H; Fullam A; Kuhn M; Zhu C; Houseman A; Somborski J; Vines A; Zhao XM; Bork P; Huerta-Cepas J; de la Fuente-Nunez C; Coelho LP
Cell; 2024 May; ():. PubMed ID: 38843834
[TBL] [Abstract][Full Text] [Related]
15. Antimicrobial Peptides-or How Our Ancestors Learned to Control the Microbiome.
Bosch TCG; Zasloff M
mBio; 2021 Oct; 12(5):e0184721. PubMed ID: 34579574
[TBL] [Abstract][Full Text] [Related]
16. Antimicrobial Peptides in the Global Microbiome: Biosynthetic Genes and Resistance Determinants.
Chen B; Zhang Z; Zhang Q; Xu N; Lu T; Wang T; Hong W; Fu Z; Penuelas J; Gillings M; Qian H
Environ Sci Technol; 2023 May; 57(20):7698-7708. PubMed ID: 37161271
[TBL] [Abstract][Full Text] [Related]
17. Models and data of AMPlify: a deep learning tool for antimicrobial peptide prediction.
Li C; Warren RL; Birol I
BMC Res Notes; 2023 Feb; 16(1):11. PubMed ID: 36732807
[TBL] [Abstract][Full Text] [Related]
18.
Van Moll L; De Smet J; Paas A; Tegtmeier D; Vilcinskas A; Cos P; Van Campenhout L
Microbiol Spectr; 2022 Feb; 10(1):e0166421. PubMed ID: 34985302
[TBL] [Abstract][Full Text] [Related]
19. Comparison of deep learning models with simple method to assess the problem of antimicrobial peptides prediction.
Lobanov MY; Slizen MV; Dovidchenko NV; Panfilov AV; Surin AA; Likhachev IV; Galzitskaya OV
Mol Inform; 2024 May; 43(5):e202200181. PubMed ID: 36961202
[TBL] [Abstract][Full Text] [Related]
20. In silico prediction and mass spectrometric characterization of botanical antimicrobial peptides.
Culver KD; Hicks LM
Methods Enzymol; 2022; 663():157-175. PubMed ID: 35168787
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]