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 2022-06-01 to 2026-06-01.)

Article	Citations
	71
Cover Picture: (Mol. Inf. 1/2023)	67
Fragment‐based deep molecular generation using hierarchical chemical graph representation and multi‐resolution graph variational autoencoder	61
A community effort in SARS‐CoV‐2 drug discovery	48
Current Insights on Skin Permeability Data and Quantitative Structure‐Property Relationship Modeling	38
Review of the 8^th autumn school in chemoinformatics	37
Cover Picture: (Mol. Inf. 1/2024)	32
Virtual screening of natural products to enhance melanogenosis	30
Predicting the duration of action of β2‐adrenergic receptor agonists: Ligand and structure‐based approaches	29
Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure‐function insights	27
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	24
Drug Search and Design Considering Cell Specificity of Chemically Induced Gene Expression Profiles for Disease‐Associated Tissues	23
LapGAT: A Semi‐Supervised Learning Framework for Drug–Target Interaction Prediction	23
Cover Picture: (Mol. Inf. 5/2024)	21
Cover Picture: (Mol. Inf. 6/2022)	18
	17
Kinematic analysis of kinases and their oncogenic mutations – Kinases and their mutation kinematic analysis	17
	16
Predicting the bandgap and efficiency of perovskite solar cells using machine learning methods	15
	15
Cover Picture: (Mol. Inf. 7/2024)	14
Neural Network Models for Prediction of Biological Activity using Molecular Dynamics Data: A Case of Photoswitchable Peptides	14
Cover Picture: (Mol. Inf. 6/2024)	13
Cover Picture: (Mol. Inf. 4/2025)	13
Cover Picture: (Mol. Inf. 11/2023)	12

Rapid Assessment of Virtually Synthesizable Chemical Structures via Support Vector Machine Models	11
Multi‐Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets**	11
Use of tree‐based machine learning methods to screen affinitive peptides based on docking data	11
Data‐driven approaches for identifying hyperparameters in multi‐step retrosynthesis	11
Natural‐Language Processing (NLP) based feature extraction technique in Deep‐Learning model to predict the Blood‐Brain‐Barrier permeability of molecules	11
Cover Picture: (Mol. Inf. 7/2025)	10
Structure–Activity Relationships and Design of Focused Libraries Tailored for Staphylococcus Aureus Inhibition	10
The VEGA web service: multipurpose online tools for molecular modelling and docking analyses	10
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
	9
Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation**	9
KNIME Workflows for Chemoinformatic Characterization of Chemical Databases	9
ADME‐DTI: Augmented Deep Meta Ensemble for Drug–Target Interaction Prediction	9
LiProS: Findable, Accessible, Interoperable, and Reusable Data Simulation Workflow to Predict Accurate Lipophilicity Profiles for Small Molecules	9
A comparison between 2D and 3D descriptors in QSAR modeling based on bio‐active conformations	8
	8
	8
Cover Picture: (Mol. Inf. 12/2023)	8
Cover Picture: (Mol. Inf. 10/2022)	8
Cover Picture: (Mol. Inf. 7/2023)	8
Deimos: A novel automated methodology for optimal grouping. Application to nanoinformatics case studies	7
Distinct binding hotspots for natural and synthetic agonists of FFA4 from in silico approaches**	7
Read‐Across Structure‐Property Relationship‐Based Superior Prediction of Fraction Unbound in Plasma from Chemical Structure: Interpretable Models with Minimum Descriptors	7
BIOMX‐DB: A web application for the BIOFACQUIM natural product database	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
	7
A Scaffold‐based Deep Generative Model Considering Molecular Stereochemical Information	7
Machine Learning in Drug Development for Neurological Diseases: A Review of Blood Brain Barrier Permeability Prediction Models	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)	6
My 50 Years with Chemoinformatics	6
Cover Picture: (Mol. Inf. 10/2025)	6
A Molecular Representation to Identify Isofunctional Molecules	6
	6
Predicting S. aureus antimicrobial resistance with interpretable genomic space maps	6
	6
Feature importance‐based interpretation of UMAP‐visualized polymer space	6
	6
Spherical GTM: A New Proposition for Visualization of Chemical Data	6
Machine Learning Models Predicting Solubility and Polymerizability of Polyimides Considering Multiple Monomers for CO ₂ Separation Membranes	6
	6
AliNA – a deep learning program for RNA secondary structure prediction	6