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Accelerating Therapeutics for Opportunities in Medicine (ATOM)

NCI-DOE Collaboration

NCI-DOE Resource Transfer Team Collaborations (NCI-DOE RTC)

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Canine_Tumor-type_classifier

Disease Target Identification

Generalized Generative Molecular Design

NCI DOE Collaboration MOSSAIC project: Population Information Integration, Analysis, and Modeling for Precision Surveillance

NCI-DOE Collaboration ADMIRRAL project: KRAS4b Protein Modeling using Multiscale Machine-Learned Modeling Infrastructure (MuMMI)

NCI-DOE Collaboration ADMIRRAL project: RAS-RAF Protein Modeling using Multiscale Machine-Learned Modeling Infrastructure (MuMMI)

NCI-DOE Collaboration Cellular Level Pilot: Predictive Modeling for Pre-Clinical Screening

NCI-DOE Collaboration IMPROVE Project: Monotherapy pan-cancer pan-drug response prediction

NCI-DOE-Collaboration ADMIRRAL project: Improving Outcomes for RAS-related Cancers

Neurocrine Histamine H1 receptor Demonstration

QMugs HOMO-LUMO Gap Prediction

Safety Screening

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3k disordered 3-component-system (DPPC-DOPC-CHOL)

Autoencoder for MD Simulation Data (P2B1)

Cancer Kinase Selectivity

Cancer Type Classifier Based on Somatic Mutations (P1B2)

Canine TUmor CLassIfication Predictor (cTULIP)

Cellular-Level Pilot Unified Drug Response Predictor (Uno)

Chemical Space Method (AutoGrow4) Demonstration

Combination Drug Response Predictor (Combo)

Curated DFT HOMO-LUMO Dataset

Drug MoA Information

Drug Molecular Descriptors

Dual Graph Convolutional Network Model to Predict Cancer Drug Response (DualGCN)

Explainable Drug Sensitivity Prediction through Cancer Pathway Enrichment Scores (PathDSP)

Gene Expression Autoencoder (P1B1)

Graph Convolutional Networks for Drug Response Prediction (GraphDRP)

H1_M2_update_10nM

Hierarchical Network for Drug Response Prediction with Attention (HiDRA)

Hybrid Graph Convolutional Network for Predicting Cancer Drug Response (DeepCDR)

Image Generator for Tabular Data (IGTD)

IMPROVE Benchmark Dataset

IMPROVE Unified Drug Response Predictor (Uno)

Integrated DataFrames of Most Prevalent Cancer Types - TopN (Top6/Top21)

KRAS4b Simulation Data

Latent Space Method (JTVAE) Demonstration

LightGBM (LGBM)

LSTM-based Clinical Text Generator (P3B2)

ML Ready Pathology Reports

MultiTask Convolutional Neural Network (MT-CNN)

Multitask DNN NLP Extraction (P3B1)

MuMMI Splash Run 2 for KRAS4b Protein Modeling

MuMMI Splash Run 4 for KRAS4b Protein Modeling

MuMMI Splash Run for RAS-RAF Protein Modeling

Normal-Tumor Pair Classifier Model (NT3)

Pathology Reports Hierarchical Self-Attention Network (HiSAN)

Pilot 1 Cancer Drug Response Prediction Dataset

Prediction of AntiCancer Compound sensitivity by means of Multi-modal Attention-based Neural Networks (PaccMann)

QMugs HOMO-LUMO Prediction Model

RAS Protein Molecular Dynamics Simulations

RNA-Seq Latent Featurizer Using Center Loss Cost Function (CLRNA)

Safety_Screen_Targets

Single Drug Response Predictor (P1B3)

Trained JTVAE Autoencoder Model on ZINC Dataset

Transformer-based Model for Predicting Cancer Drug Response (DeepTTC)

TULIP (TUmor cLassIfication Predictor)

Tumor Classifier Model (TC1)

Twin Convolutional Neural Network for drugs in SMILES format (tCNNS)

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Yes

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