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[HTML][HTML] Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learning

HT Rube, C Rastogi, S Feng, JF Kribelbauer, A Li… - Nature …, 2022 - nature.com
Protein–ligand interactions are increasingly profiled at high throughput using affinity
selection and massively parallel sequencing. However, these assays do not provide the …
被引用次数：66 相关文章

Prediction of protein-ligand binding affinity from sequencing data with interpretable machine learning

HT Rube, C Rastogi, S Feng… - Nature …, 2022 - pubmed.ncbi.nlm.nih.gov
Protein-ligand interactions are increasingly profiled at high throughput using affinity
selection and massively parallel sequencing. However, these assays do not provide the …

[引用][C] Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learning

HT Rube - 2023 Spring Western Sectional Meeting - meetings.ams.org

Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learning

HT Rube, C Rastogi, S Feng, JF Kribelbauer, A Li… - paper.sciencenet.cn
Protein–ligand interactions are increasingly profiled at high throughput using affinity
selection and massively parallel sequencing. However, these assays do not provide the …
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[HTML][HTML] Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learning

HT Rube, C Rastogi, S Feng, JF Kribelbauer… - Nature …, 2022 - ncbi.nlm.nih.gov
Protein–ligand interactions are increasingly profiled at high throughput using affinity
selection and massively parallel sequencing. However, these assays do not provide the …

Prediction of protein-ligand binding affinity from sequencing data with interpretable machine learning.

HT Rube, C Rastogi, S Feng, JF Kribelbauer… - Nature …, 2022 - europepmc.org
Protein–ligand interactions are increasingly profiled at high throughput using affinity
selection and massively parallel sequencing. However, these assays do not provide the …