Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-mass-spectrometry-ml
Awesome papers and codes list of analytical chemistry-related deep learning methods
https://github.com/JosieHong/awesome-mass-spectrometry-ml
Last synced: about 3 hours ago
JSON representation
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Databases
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- OC20 & OC22
- QM9
- GEOM - empirical density functional theory (DFT).
- MD17 & MD22 - 500 K with 1 fs resolution, and energy and forces calculated using PBE+MBD theory.
- PCQM4Mv2 - calculated HOMO-LUMO energy gaps of molecules using their 2D graphs, a significant task due to the expense of obtaining 3D equilibrium structures.
- MoleculeNet - ROC, AUC-PRC, RMSE, and MAE.
- NIST23
- MoNA - silico libraries, as well as from user contributions.
- GNPS - based mass spectrometry ecosystem that aims to be an open-access knowledge base for the community-wide organization and sharing of raw, processed, or annotated fragmentation mass spectrometry data (MS/MS).
- RepoRT
- QM9
- QM9
- QM9
- HMDB 5.0
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- SMRT - phase chromatography retention time dataset, covering up to 80,038 small molecules.
- AllCCS
- SMRT - phase chromatography retention time dataset, covering up to 80,038 small molecules.
- QM9
- AllCCS
- QM9
- QM9
- QM9
- QM9
- QM9
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- QM9
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- SMRT - phase chromatography retention time dataset, covering up to 80,038 small molecules.
- AllCCS
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- SMRT - phase chromatography retention time dataset, covering up to 80,038 small molecules.
- QM9
- AllCCS
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- SMRT - phase chromatography retention time dataset, covering up to 80,038 small molecules.
- AllCCS
- QM9
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- SMRT - phase chromatography retention time dataset, covering up to 80,038 small molecules.
- AllCCS
- QM9
- SMRT - phase chromatography retention time dataset, covering up to 80,038 small molecules.
- AllCCS
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- QM9
- QM9
- QM9
- QM9
- QM9
- QM9
- AllCCS2
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
- QM9
- QM9
- QM9
- SMRT - phase chromatography retention time dataset, covering up to 80,038 small molecules.
- AllCCS
- METLIN-CCS - CCS database includes collision cross section (CCS) values derived from IMS data for more than 27,000 molecular standards across 79 chemical classes.
-
Papers
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Mass spectrometry-related properties prediction <a id="ms_prop_prediction"></a>
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Mach. Intell. 2023
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2024
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Anal. Chem. 2023 - ms.ca/users/sign_in)
- Nat. Mach. Intell. 2023
- Bioinformatics 2024 - Transformer)
- J. Chromatogr. A 2023 - RT)
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- NeurIPS 2023 - pred)
- Bioinformatics 2023
- Anal. Chem. 2021
- ACS Cent. Sci. 2019 - research/deep-molecular-massspec)
- Anal. Chem. 2021 - Yang/GNN-RT)
- Anal. Chem. 2020
- Anal. Chem. 2022
- Anal. Chem. 2021
- Anal. Chem. 2019
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Mach. Intell. 2023
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Anal. Chem. 2019
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Anal. Chem. 2021 - Yang/GNN-RT)
- Anal. Chem. 2020
- Anal. Chem. 2024
- Anal. Chem. 2022
- Anal. Chem. 2022
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
-
Small molecular representation learning
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Chem. Sci. 2022 - bird/retrosynthesis)
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- ICLR 2023 - corp/Uni-Mol)
- PMLR 2021 - machine-learning/schnetpack)
- NeurIPS 2017 - machine-learning/SchNet)
- Brief. Bioinformatics 2024 - create/BatmanNet)
- Bioinformatics 2023
- ICLR 2023 - BERT/tree/2feff8a33e3634b66b7408e2e2780fc9d960909f)
- ICLR 2023 (spotlight) - training-via-denoising)
- ICLR 2023
- ICLR 2022
- NeurIPS 2021
- NeurIPS 2020 - ailab/grover)
- ICLR 2020
- AAAI 2023
- NeurIPS 2022
- ICLR 2022
- ICLR 2022
- ICLR 2022
- Nat. Mach. Intell. 2022
- NeurIPS 2021 - DAML/gemnet_pytorch)
- NeurIPS 2020
- ICLR 2020
- Chem. Mater 2019
- PMLR 2017 - research/mpnn)
- NeurIPS 2015 - fingerprint)
- NeurIPS 2020 - Lab/GraphCL)
- ICLR 2020 - stanford/pretrain-gnns/)
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- BCB 2019 - smile/SMILES-BERT)
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Patterns 2022 - guzik-group/selfies)
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Nat. Mach. Intell. 2022
- Chem. Mater 2019
- Nat. Mach. Intell. 2022
-
Mass spectra representation learning and matching
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- J. Cheminform. 2021
- Anal. Chem. 2019
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Anal. Chem. 2023
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
- Nat. Commun 2023 - Yang/FastEI)
-
Chemical formula prediction from mass spectra
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- JCIM 2023 - cf)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2019 - lab/sirius)
- Nat. Methods 2023
- Nat. Methods 2023
-
Discussions in database
-
Small molecules identification
-
Analytical chemistry-related properties prediction <a id="analytical_chem_prediction"></a>
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Commun 2020
- Nat. Mach. Intell. 2023
- Nat. Commun 2019 - based_retention_time_prediction/8038913)
- Nat. Mach. Intell. 2023
- Nat. Commun 2020
-
Survey papers
-
Discussions in pre-train models
-
Small molecular generation <a id="small_molecular_generation"></a>
- NeurIPS 2018
- Sci. Adv. 2018
- ICLR 2022 (Oral)
- NeurIPS 2022 - diffusion)
- TMLR 2022
- NeurIPS 2021
- ICML 2021
- ICML 2021 - ICML21)
- ICLR 2021 - ConfGen)
- NeurIPS 2020
- ICML 2020
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- ICLR 2022 (Oral)
- ICML 2021 - main/dig/ggraph/GraphDF)
- ICML 2020 - jin/multiobj-rationale)
- ICLR 2020
- ICML 2020 - jin/hgraph2graph/)
- arXiv 2019 - research/graph-nvp)
- NeurIPS 2018
- NeurIPS 2018
- ICML 2018 - jin/icml18-jtnn)
- ICML 2018 - decao/MolGAN)
- Chem. Sci. 2021 - guzik-group/stoned-selfies)
- arXiv 2018
- J Chem Inf Model 2018
- ACS Cent. Sci. 2018 - vae) 😢 No official codes are available.
- ACS Cent. Sci. 2018 - generator) 😢 No official codes are available.
- ICML/PMLR 2017
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Sci. Rep. 2019 - dl/dl4chem-geometry)
- Front. Pharmacol. 2020
- Sci. Rep. 2019 - dl/dl4chem-geometry)
-
Small molecular optimization <a id="small_molecular_optimization"></a>
- ICLR 2019 - jin/iclr19-graph2graph)
- Sci. Rep. 2019 - research/google-research/tree/master/mol_dqn)
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Mass spectra matching
- Nat. Commun 2023 - Yang/FastEI)
- PLoS Comput. Biol. 2021
-
-
Machine learning in small molecules chromatography
-
Chemical formula prediction from mass spectra
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- J. Sep. Sci. 2018
- J. Chromatogr. A 2016
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Anal. Chem. 2024
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
- Nat. Commun 2023 - Time-Prediction-for-Chromatographic-Enantioseparation/tree/main/code)
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Related awesome lists
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Chemical formula prediction from mass spectra
- Awesome Small Molecule Machine Learning
- Awesome Python Chemistry - based frameworks, libraries, software, and resources in the field of Chemistry.
- Awesome DeepBio - biology](https://github.com/hussius/deeplearning-biology): These repositories focus on deep learning methods in biology.
- awesome-pretrain-on-molecules
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-
Categories
Sub Categories
Small molecular representation learning
113
Mass spectrometry-related properties prediction <a id="ms_prop_prediction"></a>
107
Chemical formula prediction from mass spectra
77
Analytical chemistry-related properties prediction <a id="analytical_chem_prediction"></a>
48
Small molecular generation <a id="small_molecular_generation"></a>
44
Mass spectra representation learning and matching
28
Survey papers
4
Small molecules identification
3
Small molecular optimization <a id="small_molecular_optimization"></a>
2
Discussions in database
2
Discussions in pre-train models
2
Mass spectra matching
2
Keywords
awesome
3
awesome-list
2
bioinformatics
2
cheminformatics
2
drug-discovery
2
chemistry
2
computational-chemistry
2
machine-learning
1
atomistic-simulations
1
molecular-dynamics
1
python-chemistry
1
quantum-chemistry
1
simulation
1
chemical-language-models
1
drug-discovery-and-development
1
finetuning
1
gnns
1
graph-representation-learning
1
molecular-representation-learning
1
molecule
1
self-supervised-learning
1
survey
1
transfer-learning
1