1 |
Designing antibodies as therapeutics. CELL. 2022 |
2 |
DeepSCM: An efficient convolutional neural network surrogate model for the screening of therapeutic antibody viscosity. COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL. 2022 |
3 |
Deep Learning in Therapeutic Antibody Development. Methods in molecular biology. 2022 |
4 |
Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.NATURE BIOMEDICAL ENGINEERING.2021 |
5 |
Predicting unseen antibodies' neutralizability via adaptive graph neural networks. Nature Machine Intelligence 2022, 4, 964-76. |
6 |
DeepSCM: An efficient convolutional neural network surrogate model for the screening of therapeutic antibody viscosity. Computational and Structural Biotechnology Journal 2022, 20, 2143-52. |
7 |
Predicting antibody binders and generating synthetic antibodies using deep learning. Mabs 2022, 14. |
8 |
Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space. Nature Communications 2022, 13. |
9 |
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. Nature Machine Intelligence 2021, 3, 936-+. |
10 |
Applications of Machine and Deep Learning in Adaptive Immunity. In: Doherty MF, Segalman RA, editors. Annual Review of Chemical and Biomolecular Engineering, Vol 12, 2021. Annual Review of Chemical and Biomolecular Engineering. 122021. p. 39-62. |
11 |
Bridging the neutralization gap for unseen antibodies. Nature Machine Intelligence 2022. |
12 |
DLAB: deep learning methods for structure-based virtual screening of antibodies. Bioinformatics 2022, 38, 377-83. |
13 |
Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain. Cell 2022, 185, 4008-+. |
14 |
Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery. Briefings in Bioinformatics 2022, 23. |
15 |
Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning. NATURE BIOMEDICAL ENGINEERING. 2021 |
16 |
Deep Learning Driven Drug Discovery: Tackling Severe Acute Respiratory Syndrome Coronavirus 2. FRONTIERS IN MICROBIOLOGY. 2021 |
17 |
DLAB: deep learning methods for structure-based virtual screening of antibodies. Bioinformatics. 2022 |
18 |
De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV-2 spike receptor binding domain (RBD). PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS. 2022 |
19 |
ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation. BIOINFORMATICS 2022 |
20 |
Advances in computational structure-based antibody design. CURRENT OPINION IN STRUCTURAL BIOLOGY. 2022 |
21 |
De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV-2 spike receptor binding domain (RBD). PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS. 2022 |
22 |
TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences. BRIEFINGS IN BIOINFORMATICS. 2022 |
23 |
Humanization of antibodies using a machine learning approach on large-scale repertoire data.BIOINFORMATICS. 2022 |
24 |
BioPhi: A platform for antibody design, humanization, and humanness evaluation based on natural antibody repertoires and deep learning. MABS. 2022 |
25 |
Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain. CELL .2022 |
26 |
Computational design of vaccine immunogens. Current Opinion in Biotechnology 2022, 78. |
27 |
D3AI-Spike: A deep learning platform for predicting binding affinity between SARS-CoV-2 spike receptor binding domain with multiple amino acid mutations and human angiotensin-converting enzyme 2. Computers in Biology and Medicine 2022, 151. |
28 |
Deep mutational scans for ACE2 binding, RBD expression, and antibody escape in the SARS-CoV-2 Omicron BA.1 and BA.2 receptor-binding domains. Plos Pathogens 2022, 18. |
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