OOIR: Observatory of International Research

Papers

(The TQCC of Molecular Informatics is 6. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-08-01 to 2026-08-01.)

Article	Citations
	83
Cover Picture: (Mol. Inf. 1/2023)	75
Fragment‐based deep molecular generation using hierarchical chemical graph representation and multi‐resolution graph variational autoencoder	68
A community effort in SARS‐CoV‐2 drug discovery	53
Current Insights on Skin Permeability Data and Quantitative Structure‐Property Relationship Modeling	44
Undersampling Techniques for Nonlinear Chemical Space Visualization	35
Review of the 8^th autumn school in chemoinformatics	34
Cover Picture: (Mol. Inf. 1/2024)	32
Virtual screening of natural products to enhance melanogenosis	31
Predicting the duration of action of β2‐adrenergic receptor agonists: Ligand and structure‐based approaches	29
Application of automated machine learning in the identification of multi‐target‐directed ligands blocking PDE4B, PDE8A, and TRPA1 with potential use in the treatment of asthma and COPD	28
LapGAT: A Semi‐Supervised Learning Framework for Drug–Target Interaction Prediction	25
Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure‐function insights	24
Drug Search and Design Considering Cell Specificity of Chemically Induced Gene Expression Profiles for Disease‐Associated Tissues	23
Cover Picture: (Mol. Inf. 5/2024)	18
Kinematic analysis of kinases and their oncogenic mutations – Kinases and their mutation kinematic analysis	18
	16
	16
Predicting the bandgap and efficiency of perovskite solar cells using machine learning methods	15
Neural Network Models for Prediction of Biological Activity using Molecular Dynamics Data: A Case of Photoswitchable Peptides	15
	15
Cover Picture: (Mol. Inf. 7/2024)	14
Cover Picture: (Mol. Inf. 4/2025)	14
Cover Picture: (Mol. Inf. 6/2024)	13
Cover Picture: (Mol. Inf. 11/2023)	12

Use of tree‐based machine learning methods to screen affinitive peptides based on docking data	12
Natural‐Language Processing (NLP) based feature extraction technique in Deep‐Learning model to predict the Blood‐Brain‐Barrier permeability of molecules	12
Data‐driven approaches for identifying hyperparameters in multi‐step retrosynthesis	11
Rapid Assessment of Virtually Synthesizable Chemical Structures via Support Vector Machine Models	11
The VEGA web service: multipurpose online tools for molecular modelling and docking analyses	10
Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation**	10
Multi‐Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets**	10
Cover Picture: (Mol. Inf. 7/2025)	10
ADME‐DTI: Augmented Deep Meta Ensemble for Drug–Target Interaction Prediction	10
	10
LiProS: Findable, Accessible, Interoperable, and Reusable Data Simulation Workflow to Predict Accurate Lipophilicity Profiles for Small Molecules	9
Discovery of a pocket network on the domain 5 of the TrkB receptor – A potential new target in the quest for the new ligands	9
Structure–Activity Relationships and Design of Focused Libraries Tailored for Staphylococcus Aureus Inhibition	9
A comparison between 2D and 3D descriptors in QSAR modeling based on bio‐active conformations	9
Design of Thermotropic Liquid Crystal Molecules With a Wide Temperature Range for the Liquid Crystal Phase Using Machine Learning	9
KNIME Workflows for Chemoinformatic Characterization of Chemical Databases	9
	8
A Scaffold‐based Deep Generative Model Considering Molecular Stereochemical Information	8
BIOMX‐DB: A web application for the BIOFACQUIM natural product database	8
Cover Picture: (Mol. Inf. 10/2022)	8
Deimos: A novel automated methodology for optimal grouping. Application to nanoinformatics case studies	8
	8
Cover Picture: (Mol. Inf. 7/2023)	8
Cover Picture: (Mol. Inf. 12/2023)	8
Predicting S. aureus antimicrobial resistance with interpretable genomic space maps	7
Identification of a PD1/PD‐L1 inhibitor by structure‐based pharmacophore modelling, virtual screening, molecular docking and biological evaluation**	7
Cover Picture: (Mol. Inf. 10/2024)	7
Cover Picture: (Mol. Inf. 8‐9/2023)	7
	7
Distinct binding hotspots for natural and synthetic agonists of FFA4 from in silico approaches**	7
In Silico Identification of Novel and Potent Inhibitors Against Mutant BRAF (V600E), MD Simulations, Free Energy Calculations, and Experimental Determination of Binding Affinity	7
Machine Learning Models Predicting Solubility and Polymerizability of Polyimides Considering Multiple Monomers for CO ₂ Separation Membranes	7
	7
Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models	7
Read‐Across Structure‐Property Relationship‐Based Superior Prediction of Fraction Unbound in Plasma from Chemical Structure: Interpretable Models with Minimum Descriptors	7
My 50 Years with Chemoinformatics	7
	6
	6
GDMol: Generative Double‐Masking Self‐Supervised Learning for Molecular Property Prediction	6
Spherical GTM: A New Proposition for Visualization of Chemical Data	6
Feature importance‐based interpretation of UMAP‐visualized polymer space	6
Cover Picture: (Mol. Inf. 10/2025)	6
A Molecular Representation to Identify Isofunctional Molecules	6
	6