ArticleJournal of chemical information and modeling2020
libmolgrid: Graphics Processing Unit Accelerated Molecular Gridding for Deep Learning Applications.
Article in Journal of chemical information and modeling, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 68 citations in OpenAlex.
- SpheronizaTor: Spherical Voxelization for Interpretable Protein Microenvironment Modeling.Computational and structural biotechnology journal · 2026Article
- Investigating the volume and diversity of data needed for generalizable antibody-antigen ΔΔG prediction.Nature computational science · 2025Article
- Nearl: extracting dynamic features from molecular dynamics trajectories for machine learning tasks.Bioinformatics (Oxford, England) · 2025Article
- GNINA 1.3: the next increment in molecular docking with deep learning.Journal of cheminformatics · 2025Article
- Physics-Guided Active Learning for New Ligand Discovery.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2025Article
- Machine learning approaches for predicting protein-ligand binding sites from sequence data.Frontiers in bioinformatics · 2025Review
- Article
- CACHE Challenge #1: Docking with GNINA Is All You Need.Journal of chemical information and modeling · 2024Article
- PharmRL: Pharmacophore elucidation with Deep Geometric Reinforcement Learning.Research square · 2024Article
- CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks.Journal of chemical information and modeling · 2024Article
- Generative artificial intelligence in drug discovery: basic framework, recent advances, challenges, and opportunities.Frontiers in pharmacology · 2024Review
- Expanding Training Data for Structure-Based Receptor-Ligand Binding Affinity Regression through Imputation of Missing Labels.ACS omega · 2023Article
- CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks.bioRxiv : the preprint server for biology · 2023Article
- Physics-Guided Deep Generative Model for New Ligand Discovery.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2023Article
- Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks.PLoS computational biology · 2023Article
- Conformational transitions and allosteric modulation in a heteromeric glycine receptor.Nature communications · 2023Article
- Latent Biases in Machine Learning Models for Predicting Binding Affinities Using Popular Data Sets.ACS omega · 2023Article
- CAT-Site: Predicting Protein Binding Sites Using a Convolutional Neural Network.Pharmaceutics · 2022Article
- Scoring Functions for Protein-Ligand Binding Affinity Prediction using Structure-Based Deep Learning: A Review.Frontiers in bioinformatics · 2022Article
- ImprovingJournal of chemical information and modeling · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
We describe libmolgrid, a general-purpose library for representing three-dimensional molecules using multidimensional arrays of voxelized molecular data. libmolgrid provides functionality for sampling batches of data suited to machine learning workflows, and it also supports temporal and spatial recurrences over that data to facilitate work with convolutional and recurrent neural networks. It was designed for seamless integration with popular deep learning frameworks and features optimized performance by leveraging graphics processing units (GPUs). libmolgrid is a free and open source project (GPLv2) that aims to democratize grid-based modeling in computational chemistry.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.