Chemical substructures that enrich for biological activity

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Items 201–300 of 394

1. Machine Learning Prediction of the Redox Activity of Quinones
   Ilia Kichev, Lyuben Borislаvov, Alia Tadjer, Radostina K. Stoyanova · 2023 · Materials
2. Phenotypic Screening of Phylomer Peptide Libraries Derived from Genome Fragments to Identify and Validate New Targets and Therapeutics
   Paul M. Watt · 2009 · Future Medicinal Chemistry
3. Automatic identification of chemical moieties
   Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus‐Robert Müller, Oliver T. Unke · 2023 · Physical Chemistry Chemical Physics
4. Exploiting uncertainty measures in compounds activity prediction using support vector machines
   Sabina Podlewska, Wojciech Marian Czarnecki, Dawid Warszycki, Andrzej Jacek Bojarski · 2014 · Bioorganic & Medicinal Chemistry Letters
5. QSAR classification of metabolic activation of chemicals into covalently reactive species
   Chin Yee Liew, Chuen Pan, Andre Tan, Ke Xin Magneline Ang, Chun Wei Yap · 2012 · Molecular Diversity
6. Investigating Metabolic Pathways and Networks
   Md. Altaf‐Ul‐Amin, Shigehiko Kanaya, Zeti‐Azura Mohamed‐Hussein · 2018 · Elsevier eBooks
7. Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study
   Rita Ortega-Vallbona, Martina Palomino‐Schätzlein, Laia Tolosa, Emilio Benfenati, Gerhard Franz Ecker, Rafael Gozalbes, Eva Serrano‐Candelas · 2024 · International Journal of Molecular Sciences
8. Bioactive iridoid glycoside isolated from Morinda tinctoria (Roxb.) roots exhibit therapeutic efficacy
   Dipita Bhakta-Guha, Akella Sivaramakrishna, Siva Ramamoorthy · 2012 · Industrial Crops and Products
9. Galactoside-Based Molecule Enhanced Antimicrobial Activity through Acyl Moiety Incorporation: Synthesis and In Silico Exploration for Therapeutic Target
   Faez Ahmmed, Samiah Hamad Al-Mijalli, Emad M. Abdallah, Ibrahim H. Eissa, Ferdausi Ali, Ajmal Rashid Bhat, Joazaizulfazli Jamalis, Taïbi Ben Hadda, Sarkar M. A. Kawsar · 2023 · Pharmaceuticals
10. Multitargeting Heterocycles
    Pankaj Kumar Singh, Om Silakari · 2018 · Elsevier eBooks
11. Acetylenic Synthetic Betulin Derivatives Inhibit Akt and Erk Kinases Activity, Trigger Apoptosis and Suppress Proliferation of Neuroblastoma and Rhabdomyosarcoma Cell Lines
    Sylwia Katarzyna Król, Ewa Bębenek, Magdalena Dmoszyńska‐Graniczka, Adrianna Sławińska-Brych, Stanisław Boryczka, Andrzej Stepulak · 2021 · International Journal of Molecular Sciences
12. A quick and low E-factor waste valorization procedure for CuCl-catalyzed oxidative self-coupling of (hetero)arylboronic acid in pomegranate peel ash extract
    Jangam Lakshmidevi, Bandameeda Ramesh Naidu, Katta Venkateswarlu, Marlia Mohd Hanafiah, Sivarama Krishna Lakkaboyana · 2022 · Green Chemistry Letters and Reviews
13. Improving Classical Substructure-Based Virtual Screening to Handle Extrapolation Challenges
    Tammy Biniashvili, Ehud Schreiber, Yossef Kliger · 2012 · Journal of Chemical Information and Modeling
14. Machine Learning Descriptors for Mapping Structure‐Property‐Performance Relationships of Perovskite Solar Cells
    Yu Su, Kongxiang Wang, Xiang Guan, Yumao Wu, Hong Zhang, Fengxian Xie, Junhao Chu · 2025 · Advanced Energy Materials
15. Fingerprint applicable for machine learning tested on LCST behavior of polymers
    Yannik Köster, Julian Kimmig, Stefan Zechel, Ulrich S. Schubert · 2023 · Cell Reports Physical Science
16. Enhancing HCV NS3 Inhibitor Classification with Optimized Molecular Fingerprints Using Random Forest
    Sema Atasever · 2025 · International Journal of Molecular Sciences
17. Identification of Potential p38γ Inhibitors via In Silico Screening, In Vitro Bioassay and Molecular Dynamics Simulation Studies
    Zixuan Cheng, Mrinal R. Bhave, Siaw San Hwang, Taufiq Rahman, Xavier Chee Wezen · 2023 · International Journal of Molecular Sciences
18. Big Data in Structure-Property Studies—From Definitions to Models
    Jarosław Polański · 2017 · Challenges and advances in computational chemistry and physics
19. Photosynthesis-Inhibiting Activity of 1-[(2-Chlorophenyl)carbamoyl]- and 1-[(2-Nitrophenyl)carbamoyl]naphthalen-2-yl Alkylcarbamates
    Tomáš Goněc, Josef Stranik, Matúš Peško, Jiří Kos, Michal Oravec, Katarína Kráľová, Josef Jampílek · 2017 · Molecules
20. Exploration of 3,6-dihydroimidazo(4,5-d)pyrrolo(2,3-b)pyridin-2(1H)-one derivatives as JAK inhibitors using various in silico techniques
    Radhakrishnan S. Jisha, Lilly Aswathy, Vijay Hariram Masand, Jayant M. Gajbhiye, Indira G. Shibi · 2017 · In Silico Pharmacology
21. Bi-modal Variational Autoencoders for Metabolite Identification Using Tandem Mass Spectrometry
    Svetlana Kutuzova, Christian Igel, Mads Eggert Nielsen, Douglas McCloskey · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
22. Semi-supervised model-based clustering with controlled clusters leakage
    Marek Śmieja, Łukasz Struski, Jacek Tabor · 2017 · Expert Systems with Applications
23. Development of New Methods Needs Proper Evaluation—Benchmarking Sets for Machine Learning Experiments for Class A GPCRs
    Damian Leśniak, Sabina Podlewska, Stanisław Jastrzȩbski, Igor Sieradzki, Andrzej Jacek Bojarski, Jacek Tabor · 2019 · Journal of Chemical Information and Modeling
24. Uncovering blood–brain barrier permeability: a comparative study of machine learning models using molecular fingerprints, and SHAP explainability
    E. Raveendrakumar, Boinapalli Gopichand, Hrushikesh Bhosale, Nidheesh Melethadathil, Jayaraman Krishnamoorthy Valadi · 2024 · SAR and QSAR in environmental research
25. Inferring Chemogenomic Features from Drug‐Target Interaction Networks
    Yoshihiro Yamanishi · 2013 · Molecular Informatics
26. Structural insights into serotonin receptor ligands polypharmacology
    Sabina Podlewska, Rafał Kafel, Enza Lacivita, Grzegorz Satała, Albert J. Kooistra, Márton Vass, Chris de Graaf, Marcello Leopoldo, Andrzej Jacek Bojarski, Stefan Mordalski · 2018 · European Journal of Medicinal Chemistry
27. Computational Approaches for Drug-Induced Liver Injury (DILI) Prediction: State of the Art and Challenges
    Olivier J. M. Béquignon, Gopal V. Pawar, Bob van de Water, M Cronin, Gerard J. P. van Westen · 2019 · Elsevier eBooks
28. Synthesis and evaluation of biarylquinoline derivatives as novel HIF-1α inhibitors
    Yu‐Chieh Wu, Meng‐Tien Lu, Tai-Hui Lin, Po‐Chen Chu, Chih‐Shiang Chang · 2022 · Bioorganic Chemistry
29. Pd-catalyzed Site-selective direct arene C H arylation of Pyrrolo[2,3-d]pyrimidine derivatives with aryl iodides
    Min Liu, Zhengtong Mao, Yunfeng Jiang, Zhuo Zhang, Xingxian Zhang · 2022 · Tetrahedron Letters
30. 4-Isoxazolyl-1,4-Dihydropyridines: A Tale of Two Scaffolds
    Nicholas R. Natale, Scott A. Steiger · 2014 · Future Medicinal Chemistry
31. Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis
    Krzysztof Rataj, Wojciech Marian Czarnecki, Sabina Podlewska, Agnieszka Pocha, Andrzej Jacek Bojarski · 2018 · Molecules
32. Drug target interaction predictions using PU- Leaming under different experimental setting for four formulations namely known drug target pair prediction, drug prediction, target prediction and unknown drug target pair prediction
    Hetal Rahul Rajpura, Alioune Ngom · 2018 · IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
33. Deep Belief Networks for Ligand-Based Virtual Screening of Drug Design
    2016 · International Workshop on Computer Science and Engineering (WCSE)
34. Übergangsmetallfreie oxidative Kreuzkupplung von Tetraarylboraten zu Biarylen mit organischen Oxidationsmitteln
    Carolin Gerleve, Armido Studer · 2020 · Angewandte Chemie
35. The topology of molecular representations and its influence on machine learning performance
    Florian Rottach, Sebastian Schieferdecker, Carsten Eickhoff · 2025 · Journal of Cheminformatics
36. Harnessing Machine Learning for the Virtual Screening of Natural Compounds as Both EGFR and HER2 Inhibitors in Colorectal Cancer: A Novel Therapeutic Approach
    Deli-Bright Nii Tettey. Oku, Damilare David Babatunde, Yannick Belo Nuapia, Garland Kgosi More, Ramakwala Christinah Chokwe · 2025 · ACS Omega
37. Stacking Ensemble Neural Network for Chemical Safety Assessment: A Case Study of Thyroid Peroxidase and Natural Product Screening
    Darlene Nabila Zetta, Tarapong Srisongkram · 2025 · ACS Omega
38. A novel solid-phase synthetic method for production of N -alkyl-4-alkylamino-1-aryl-1 H -pyrazolo[3,4- d ]pyrimidine-6-carboxamide library
    Yun-Jeong Heo, Moon‐Kook Jeon · 2017 · Tetrahedron
39. Algorithm for Predicting Compound Protein Interaction Using Tanimoto Similarity and Klekota-roth Fingerprint
    Isnan Mulia, Wisnu Ananta Kusuma, Farit Mochamad Afendi · 2018 · TELKOMNIKA (Telecommunication Computing Electronics and Control)
40. FP-MAP: an extensive library of fingerprint-based molecular activity prediction tools
    Vishwesh Venkatraman · 2023 · Frontiers in Chemistry
41. Quantitative structure-retention relationships for pyridinium-based ionic liquids used as gas chromatographic stationary phases: convenient software and assessment of reliability of the results
    Anastasia Yu. Sholokhova, Dmitriy D. Matyushin, М. В. Шашков · 2024 · Journal of Chromatography A
42. Deep belief networks using hybrid fingerprint feature for virtual screening of drug design
    Aries Fitriawan, Ito Wasito, Arida Ferti Syafiandini, Mukhlis Amien, Arry Yanuar · 2016 · International Conference on Advanced Computer Science and Information Systems
43. Molecular Similarity in Computational Toxicology
    Matteo Floris, Stefania Olla · 2018 · Methods in molecular biology
44. AFM–SEIRA nanospectroscopy imaging of the drug adsorption on the PtNP monolayers
    Natalia Piergies, Magdalena Oćwieja, Marta Sadowska, Dorota Duraczyńska, Małgorzata Nattich-Rak, Bogna Daria Napruszewska · 2024 · Measurement
45. MetaCGRP is a high-precision meta-model for large-scale identification of CGRP inhibitors using multi-view information
    Nalini Schaduangrat, Phisit Khemawoot, Apisada Jiso, Phasit Charoenkwan, Watshara Shoombuatong · 2024 · Scientific Reports
46. Computational Methods for Predicting Chemical Reactivity of Covalent Compounds
    Zhe Zhang, Ruyu Gao, Meiling Zhao, Xiangying Zhang, Haotian Gao, Yifei Qi, Renxiao Wang, Yan Li · 2025 · Journal of Chemical Information and Modeling
47. RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction
    Yemin Yu, Luotian Yuan, Ying Wei, Hanyu Gao, Fei Qing Wu, Zhihua Wang, Xinhai Ye · 2024 · Proceedings of the AAAI Conference on Artificial Intelligence
48. Extraction and validation of substructure profiles for enriching compound libraries
    Wee Kiang Yeo, Mei‐Lin Go, Shahul Nilar · 2012 · Journal of Computer-Aided Molecular Design
49. - Library Design, Chemical Space, and Drug Likeness
    Hugo O. Villar · 2015 · CRC Press eBooks
50. Voting-based ensemble method for prediction of bioactive molecules
    Olutomilayo Olayemi Petinrin, Faisal Saeed, Tawfik Al-Hadhrami · 2017 · IEEE International Conference on Knowledge Engineering and Applications (ICKEA)
51. Bioactive molecule prediction using majority voting-based ensemble method
    Olutomilayo Olayemi Petinrin, Faisal Saeed · 2018 · Journal of Intelligent & Fuzzy Systems
52. Quantum Chemical Evaluation on the Structure, Spectroscopic, QSAR Modeling and Topological Insight of Nuarimol
    R. Godwini, J. Clemy Monicka, S. Grace Victoria · 2023 · Polycyclic aromatic compounds
53. Quantitative structure-activity and toxicity relationship study of CCRF-CEM and RPMI 8402 cell line apoptosis with some anticancer compounds
    David Ebuka Arthur, Adamu Uzairu, Paul Andrew Mamza, Abechi Eyeji Stephen, Gideon Adamu Shallangwa · 2017 · Chemical Data Collections
54. SimCAL: a flexible tool to compute biochemical reaction similarity
    Tadi Venkata Sivakumar, Anirban Bhaduri, Rajasekhara Reddy Duvvuru Muni, Jin Hwan Park, Tae Yong Kim · 2018 · BMC Bioinformatics
55. ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery
    Andaç Demir, Barış Coşkunuzer, Ignacio Segovia-Domínguez, Yuzhou Chen, Yulia R. Gel, Bülent Kızıltan · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
56. Molecular Fingerprints Optimization for Enhanced Predictive Modeling
    Viktoriia Turkina, Melanie R.W. Messih, Etienne Kant, Jelle T. Gringhuis, Annemieke Petrignani, Garry L. Corthals, Jake William O'Brien, Saer Samanipour · 2024 · ChemRxiv
57. Inhibition potential of margolonone and isomargolonone against the dengue virus protease using molecular modeling approaches
    Gourav Choudhir, Faiza Iram, Israil, Mohammad Shahid, Anas Shamsi, Md. Imtaiyaz Hassan, Asimul Islam · 2025 · Frontiers in Bioinformatics
58. Prediction of the effects of small molecules on the gut microbiome using machine learning method integrating with optimal molecular features
    Binyou Wang, Jianmin Guo, Xiaofeng Liu, Yang Yu, Jianming Wu, Yiwei Wang · 2023 · BMC Bioinformatics
59. PROFIS: Design of Target-Focused Libraries by Probing Continuous Fingerprint Space with Recurrent Neural Networks
    Hubert Rybka, Tomasz Danel, Sabina Podlewska · 2025 · Journal of Chemical Information and Modeling
60. Increasing the Scale of the Mass Spectrometry Query Language Compendium with Explainable AI
    Thomas V. Harwood, Mingxun Wang, Trent R. Northen, Benjamin P. Bowen · 2025 · Analytical Chemistry
61. UniPert-G2CP bridges genetic and chemical screens from molecular representation to phenotype modeling
    Yiming Li, Min De ZENG, Jun Zhu, Linjing Liu, Fang Wang, L L Huang, Fan Yang, Min Li, Jianhua Yao · 2026 · Cell
62. Linear and Kernel Model Construction Methods for Predicting Drug–Target Interactions in a Chemogenomic Framework
    Yoshihiro Yamanishi · 2018 · Methods in molecular biology
63. Multi-label classification using deep belief networks for virtual screening of multi-target drug
    Aries Fitriawan, Ito Wasito, Arida Ferti Syafiandini, Mukhlis Amien, Arry Yanuar · 2016 · International Conference on Computer, Control, Informatics and its Applications
64. APDB: a database on air pollutant characterization and similarity prediction
    Eva Viesi, Davide Stefano Sardina, Ugo Perricone, Rosalba Giugno · 2023 · Database
65. Metal-free synthesis of biarenes via photoextrusion in di(tri)aryl phosphates
    Hisham Qrareya, Lorenzo Meazza, Stefano Protti, Maurizio Fagnoni · 2020 · Beilstein Journal of Organic Chemistry
66. Supervised topic modeling for predicting molecular substructure from mass spectrometry
    Gabriel K. Reder, Adamo Young, Jaan Altosaar, Jakub Rajniak, Noémie Elhadad, Michael Andrew Fischbach, Susan Holmes · 2021 · F1000Research
67. Predicting the Enzymatic Hydrolysis Half‐lives of New Chemicals Using Support Vector Regression Models Based on Stepwise Feature Elimination
    Wan Xiang Shen, Tao Xiao, Shangying Chen, Feng Liu, Yu Chen, Yuyang Jiang · 2017 · Molecular Informatics
68. De novo Molecular Design using Deep Learning
    Thanh‐Hoang Nguyen‐Vo · 2024 · Open Access Victoria University of Wellington | Te Herenga Waka (Figshare)
69. Establishing the foundations for a data-centric AI approach for virtual drug screening through a systematic assessment of the properties of chemical data
    Allen Chong, Ser-Xian Phua, Yunzhi Xiao, Woon Yee Ng, HY Li, Wilson Wen Bin Goh · 2024 · eLife
70. Construction of Biaryl Sulfonamides via Pd(II)-Catalyzed Cross-Coupling of C(sp 2 )-H Bonds with Iodobenzenesulfonamides
    Debabrata Bhattacharya, Sampurna Pal, Indranil Banerjee, Srinivasarao Arulananda Babu · 2025 · ACS Omega
71. Active Stacking-Deep Learning with Strategic Sampling for Small and Imbalanced Chemical Toxicity Prediction
    Darlene Nabila Zetta, Watshara Shoombuatong, Tarapong Srisongkram · 2025 · ACS Omega
72. Structure-guided discovery of ubiquitin-specific protease 7 inhibitors through integrative quantitative structure-activity relationship modeling, docking, and molecular dynamics
    Muhammad Shahab, Muhammad Salman Waqas, Aamir Fahira, Haoke Zhang, Zunnan Huang · 2025 · Computers in Biology and Medicine
73. Explainable AI-driven prediction of influenza neuraminidase inhibitors using a stacked ensemble-learning framework
    Ittipat Meewan, Nalini Schaduangrat, Lawankorn Mookdarsanit, Pakpoom Mookdarsanit, Watshara Shoombuatong · 2025 · Computers in Biology and Medicine
74. Molecular graph-based invariant representation learning with environmental inference and subgraph generation for out-of-distribution generalization
    Hang Zhu, Sisi Yuan, Mingjing Tang, Guifei Zhou, Zhanxuan Hu, Zhaoyang Liu, Jin Li, Jianmin Wang, Chunyan Li · 2026 · Journal of Cheminformatics
75. Investigation of bacterial DNA gyrase Inhibitor classification models and structural requirements utilizing multiple machine learning methods
    Guozheng Zhou, Yan Li · 2024 · Molecular Diversity
76. Gram matrix: an efficient representation of molecular conformation and learning objective for molecular pretraining
    Wenkai Xiang, Feisheng Zhong, Lin Ni, Mingyue Zheng, Xutong Li, Qian Shi, Dingyan Wang · 2024 · Briefings in Bioinformatics
77. Advancing Molecule Invariant Representation via Privileged Substructure Identification
    Ruijia Wang, H. X. Dai, Cheng Hong Yang, Le Song, Chuan Shi · 2024 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
78. BRAFPred: A Novel Approach for Accurate Prediction of the B-Type Rapidly Accelerated Fibrosarcoma Inhibitor
    Ming Zhang, Chaoming Zhang, Keyu Liu, Xibei Yang, Xiaojian Liu, Fang Ge · 2025 · ACS Omega
79. Computer-Aided Discovery of Natural Compounds Targeting the ADAR2 dsRBD2-RNA Interface and Computational Modeling of Full-Length ADAR2 Protein Structure
    Carolyn N. Ashley, Emmanuel Broni, Michelle Pena-Martinez, Chanyah M. Wood, Samuel K. Kwofie, Whelton A. Miller · 2025 · International Journal of Molecular Sciences
80. DeepHDAC3i: Leveraging an Interpretable Deep Learning-Based Framework for the Accelerated Discovery of HDAC3 Inhibitors
    Saeed Ahmad, Nalini Schaduangrat, Ittipat Meewan, Watshara Shoombuatong · 2025 · IEEE Transactions on Computational Biology and Bioinformatics
81. Practical application of the Average Information Content Maximization (AIC-MAX) algorithm: selection of the most important structural features for serotonin receptor ligands
    Dawid Warszycki, Marek Śmieja, Rafał Kafel · 2017 · Molecular Diversity
82. Computational strategies towards developing novel antimelanogenic agents
    P. Ambili Unni, Sajitha Lulu S, Girinath G. Pillai · 2020 · Life Sciences
83. Data types and resources
    Stephanie Kay Ashenden, Sumit Deswal, Krishna C. Bulusu, Aleksandra Bartosik, Khader Shameer · 2021 · Elsevier eBooks
84. Thiazolyl-substituted porphyrins as standards for singlet molecular oxygen photosensitization
    Marek Scholz, Roman Dĕdic, Miriam Miguel, Rodolfo Lavilla, Santi Nonell · 2011 · Journal of Porphyrins and Phthalocyanines
85. Physicochemical Property Labels as Molecular Descriptors for Improved Analysis of Compound–Protein and Compound–Compound Networks
    Masaaki Kotera · 2018 · Methods in molecular biology
86. Machine learning–based QSAR for safety evaluation of environmental chemicals
    Yuchen Gao, Jiachen Zhang, Shixuan Cui, Yiqu Wu, Mei‐Ling Huang, Shulin Zhuang · 2023 · Elsevier eBooks
87. Prompting Meta-Learned Hierarchical Graph Network for Molecular Property Prediction
    Xiang Zhuang, Keyan Ding, Yin Fang, Huajun Chen, Qiang Zhang · 2023 · IEEE International Conference on Medical Artificial Intelligence (MedAI)
88. Deep cross-modal learning between tandem mass spectrometry and molecular fingerprints for metabolite identification
    Chao‐Fu Wang, Ping Xu, Lingyun Xue, Yian Liu, Ming Yan, Anqi Chen, Shundi Hu, Luhong Wen · 2024 · International Journal of Mass Spectrometry
89. ACSMPred-FRL: Accelerating the Identification of Anticancer Small Molecules Using Feature Representation Learning
    Watshara Shoombuatong, Nalini Schaduangrat, Lawankorn Mookdarsanit, S. M. Hasan Mahmud, Kanthida Kusonmano, Pakpoom Mookdarsanit · 2025 · IEEE Access
90. Insights into the antineoplastic mechanism of Chelidonium majus via systems pharmacology approach
    Xinzhe Xiao, Zehui Chen, Zengrui Wu, Tianduanyi Wang, Weihua Li, Guixia Liu, Bo Zhang, Yun Tang · 2019 · Quantitative Biology
91. Analisis Gerombol Simultan dan Jejaring Farmakologi antara Senyawa dengan Protein Target pada Penentuan Senyawa Aktif Jamu Anti Diabetes Tipe 2
    Nurul Qomariasih, Budi Susetyo, Farit Mochamad Afendi · 2016 · Jurnal Jamu Indonesia
92. Library Design, Chemical Space, and Drug Likeness
    Hugo O. Villar · 2015 · CRC Press eBooks
93. In-silico prediction of anti-breast cancer activity of ginger (Zingiber officinale) using machine learning techniques
    Marisca Evalina Gondokesumo, Muhammad Rezki Rasyak · 2024 · Breast Disease
94. Prediction of the heats of combustion for food-related organic compounds. A quantitative structure–property relationship (QSPR) study
    Mario G. Díaz, Frida V. Dimarco Palencia, Matías F. Andrada, Esteban G. Vega Hissi, Pablo R. Duchowicz, Juan Ceferino Garro Martinez · 2024 · Journal of Thermal Analysis and Calorimetry
95. ML-based Models as a Strategy to Discover Novel Antiepileptic Drugs Targeting Sodium Receptor Channel
    Priyanka Andola, Mukesh Doble · 2024 · Current Topics in Medicinal Chemistry
96. Deep Learning-Based Molecular Fingerprint Prediction for Metabolite Annotation
    Hoi Yan Katharine Chau, Xinran Zhang, Habtom W. Ressom · 2025 · Metabolites
97. Discovering Drug-Protein Interactions Based on their Fingerprints
    Weimin Luo, Keith C. C. Chan · 2011 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
98. Structural elucidation of a series of 6‐methyl‐3‐carboxamidocoumarins
    André Fonseca, Alexandra Gaspar, María João Matos, Lígia R. Gomes, John Nicolson Low, Eugenio Uriarte, Fernanda Borges · 2016 · Magnetic Resonance in Chemistry
99. On Modeling Objects Using Sequence of Moment Invariants
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100. Mutual Support of Ligand- and Structure-Based Approaches—To What Extent We Can Optimize the Power of Predictive Model? Case Study of Opioid Receptors
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