yusuke1997/dblp-id-title huggingface dataset:
Discovery of Small Molecule Inhibitors of Protein-Protein Interactions Using Combined Ligand and Target Score Normalization
Are "GAPT Charges" Really Just Charges?
In Vitro Drug Sensitivity-Gene Expression Correlations Involve a Tissue of Origin Dependency
Enhancing Permeability Prediction of Heterobifunctional Degraders Using Machine Learning and Metadynamics-Informed 3D Molecular Descriptors
Beyond Terrestrial Biology: Charting the Chemical Universe of α-Amino Acid Structures
The Rapra Abstracts Rubber and Plastics Database
Viscosity Prediction of Lubricants by a General Feed-Forward Neural Network
Structure-Based Virtual Screening Identifies Novobiocin, Montelukast, and Cinnarizine as TRPV1 Modulators with Anticonvulsant Activity In Vivo
Exploring the Limits of the Generalized CHARMM and AMBER Force Fields through Predictions of Hydration Free Energy of Small Molecules
Staphylococcus aureus Bicomponent gamma-Hemolysins, HlgA, HlgB, and HlgC, Can Form Mixed Pores Containing All Components
Distributed Chemical Computing Using ChemStar: An Open Source Java Remote Method Invocation Architecture Applied to Large Scale Molecular Data from PubChem
Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning
Structural selectivity of topological indexes in alkane series
Deriving three-dimensional representations of molecular structure from connection tables augmented with configuration designations using distance geometry
A Multitask Approach to Learn Molecular Properties
Data-Driven Score-Based Models for Generating Stable Structures with Adaptive Crystal Cells
Enhanced Virtual Screening by Combined Use of Two Docking Methods: Getting the Most on a Limited Budget
Enumeration and Classification of Certain Polygonal Systems Representing Polycyclic Conjugated Hydrocarbons: Annelated Catafusenes
Plausible Paths in the Rearrangement Reaction of Polycyclic Hydrocarbons Searched by the Graph-Theoretical Method and Computer Techniques
Endocrine Disruptome - An Open Source Prediction Tool for Assessing Endocrine Disruption Potential through Nuclear Receptor Binding
Gain-of-Function SHP2 E76Q Mutant Rescuing Autoinhibition Mechanism Associated with Juvenile Myelomonocytic Leukemia
Machine Learning Models to Predict Inhibition of the Bile Salt Export Pump
Unified Deep Learning of Molecular and Protein Language Representations with T5ProtChem
ConfGen: A Conformational Search Method for Efficient Generation of Bioactive Conformers
Molecular Complexity and Its Impact on the Probability of Finding Leads for Drug Discovery
Combining Virtual Reality Visualization with Ensemble Molecular Dynamics to Study Complex Protein Conformational Changes
Resolved Fluorescence Emission Spectra of PRODAN in Ethanol/Buffer Solvents
Predicted Structures and Dynamics for Agonists and Antagonists Bound to Serotonin 5-HT2B and 5-HT2C Receptors
Application of a Pruning Algorithm To Optimize Artificial Neural Networks for Pharmaceutical Fingerprinting
chemicalize.org
Enhancing the Hit-to-Lead Properties of Lead Optimization Libraries
Ligand Binding Mode Prediction by Docking: Mdm2/Mdmx Inhibitors as a Case Study
Theoretical Studies on DNA-Cleavage Mechanism of Copper(II) Complexes: Probing Generation of Reactive Oxygen Species
25 Years of Science Citation Index - some experiences
Knowledge-Based Strategy to Improve Ligand Pose Prediction Accuracy for Lead Optimization
Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field
Three-Dimensional Shape-Based Searching of Conformationally Flexible Compounds
Evaluation and Application of Isokinetic Relationships: The Thermal Decomposition of Solids under Nonisothermal Conditions
CSAR Scoring Challenge Reveals the Need for New Concepts in Estimating Protein-Ligand Binding Affinity
MCSS: a new algorithm for perception of maximal common substructures and its application to NMR spectral studies. 2. Applications
Digital computers in electrochemistry
Genetic Function Approximation Experimental Design (GFAXD): A New Method for Experimental Design
A systematic representation of analytical chemical actions
Investigation on the Effect of Key Water Molecules on Docking Performance in CSARdock Exercise
Evaluating Virtual Screening Methods: Good and Bad Metrics for the "Early Recognition" Problem
Study on the Assembly Mechanisms and Transport Properties of Transmembrane End-Charged Cyclic Peptide Nanotubes
Coordination of Na + by Monoamine Ligands in Dopamine, Norepinephrine, and Serotonin Transporters
Experimental and Computational Prediction of Glass Transition Temperature of Drugs
Algorithms for unique and unambiguous coding and symmetry perception of molecular structure diagrams. 5. Unique coding by the method of orbit graphs
Application of Random Forest Approach to QSAR Prediction of Aquatic Toxicity
Introduction of the Conditional Correlated Bernoulli Model of Similarity Value Distributions and its Application to the Prospective Prediction of Fingerprint Search Performance
Docking of ATP to Ca-ATPase: Considering Protein Domain Motions
CHARMM-GUI Micelle Builder for Pure/Mixed Micelle and Protein/Micelle Complex Systems
MecDDI: Clarified Drug-Drug Interaction Mechanism Facilitating Rational Drug Use and Potential Drug-Drug Interaction Prediction
Genetic Parameterization of Interfacial Force Fields Based on Classical Bulk Force Fields and Ab Initio Data: Application to the Methanol-ZnO Interfaces
Descriptions and Implementations of DL_F Notation: A Natural Chemical Expression System of Atom Types for Molecular Simulations
Hierarchical Graph Attention Network with Positive and Negative Attentions for Improved Interpretability: ISA-PN
Generation of molecular graphs for QSAR studies: an approach based on acyclic fragment combinations
Semiautomatic indexing of structured information of text
Explainable Solvation Free Energy Prediction Combining Graph Neural Networks with Chemical Intuition
Exploring Functional Group Transformations on CASREACT
Matched Peptides: Tuning Matched Molecular Pair Analysis for Biopharmaceutical Applications
Influence of Alkali Metal Cations upon the Kolbe-Schmitt Reaction Mechanism
Accurate and Efficient Calculation of Protein-Protein Binding Free Energy-Interaction Entropy with Residue Type-Specific Dielectric Constants
On Outliers and Activity Cliffs-Why QSAR Often Disappoints
Non-Covalent π-Stacking Interactions between Asphaltene and Porphyrin in Bitumen
Toward Compilation of Balanced Protein Stability Data Sets: Flattening the ΔΔ G Curve through Systematic Enrichment
Comparative Analysis of TCR and TCR-pMHC Complex Structure Prediction Tools
Are Thermodynamic and Kinetic Stabilities Correlated? A Topological Index of Reactivity toward Electrophiles Used as a Criterion of Aromaticity of Polycyclic Benzenoid Hydrocarbons
StructRank: A New Approach for Ligand-Based Virtual Screening
AiZynthTrain: Robust, Reproducible, and Extensible Pipelines for Training Synthesis Prediction Models
Refinement and Truncation of DNA Aptamers Based on Molecular Dynamics Simulations: Computational Protocol and Experimental Validation
New Perspectives in Computer-Assisted Formal Synthesis Design-Treatment of Delocalized Electrons
Protecting Inventions in Chemistry: Commentary on Chemical Case Law under the European Patent Convention and the German Patent Law By Dr. Bernd Hansen and Dr. Fritjoff Hirsch. Wiley-VCH: New York, 1997, 511 pp, 3-527-28808-2
Hydrogen Bonding and π-Stacking: How Reliable are Force Fields? A Critical Evaluation of Force Field Descriptions of Nonbonded Interactions
ATBdiscrimination: An in Silico Tool for Identification of Active Tuberculosis Disease Based on Routine Blood Test and T-SPOT.TB Detection Results
Chemical Space of Molecular Nanomotors: Optimizing Photochemical Properties for One- and Two-Photon Applications
Molecular Modeling of Catalysts and Catalytic Reactions
Automated Chemical Reaction Extraction from Scientific Literature
AROPS: A Framework of Automated Reaction Optimization with Parallelized Scheduling
Symmetry of chemical structures: A novel method of graph automorphism group determination
Comparative Structural Connectivity Spectra Analysis (CoSCoSA) Models of Steroid Binding to the Corticosteroid Binding Globulin
Ensemble-Based Docking Using Biased Molecular Dynamics
Predicting Collision Cross-Section Values for Small Molecules through Chemical Class-Based Multimodal Graph Attention Network
WordPerfect Office X6 Software Review
Binding of Fatty Acids to beta-Cryptogein: Quantitative Structure-Activity Relationships and Design of Selective Protein Mutants
MGT: Machine Learning Accelerates Performance Prediction of Alloy Catalytic Materials
Discovery of Small Molecule CD40-TRAF6 Inhibitors
Identification of Hits and Lead Structure Candidates with Limited Resources by Adaptive Optimization
Correlation-Based Framework for Extraction of Insights from Quantum Chemistry Databases: Applications for Nanoclusters
Integrating Protein Interaction Surface Prediction with a Fragment-Based Drug Design: Automatic Design of New Leads with Fragments on Energy Surfaces
CageCavityCalc ( C 3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages
Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation
Machine-Guided Polymer Knowledge Extraction Using Natural Language Processing: The Example of Named Entity Normalization
Quantitative Structure-Activity Relationship Studies on Inhibition of HERG Potassium Channels
QM/MM Studies of Dph5 - A Promiscuous Methyltransferase in the Eukaryotic Biosynthetic Pathway of Diphthamide
Structural Perspective on the Direct Inhibition Mechanism of EGCG on Mammalian Histidine Decarboxylase and DOPA Decarboxylase
Performance and Analysis of the Alchemical Transfer Method for Binding-Free-Energy Predictions of Diverse Ligands
I-DNAN6mA: Accurate Identification of DNA N 6 -Methyladenine Sites Using the Base-Pairing Map and Deep Learning
Online search strategies for semiconductor or superconductor materials
CANDID-CNS: AI Unlocks Stereochemistry and Beyond Rule of 5 to Predict CNS Penetration of Small Molecules
AGDIFF: Attention-Enhanced Diffusion for Molecular Geometry Prediction
A Novel Definition of the Overall Hyper-Wiener Index for Unsaturated Hydrocarbons
Stacking Interactions of Druglike Heterocycles with Nucleobases
Identification of Noncompetitive Protein-Ligand Interactions for Structural Optimization
Characterization of Differential Dynamics, Specificity, and Allostery of Lipoxygenase Family Members
Emerging Pattern Mining To Aid Toxicological Knowledge Discovery
Summary of the history and status of the system development for the Environmental Chemicals Data and Information Network (ECDIN)
Signal-3L 2.0: A Hierarchical Mixture Model for Enhancing Protein Signal Peptide Prediction by Incorporating Residue-Domain Cross-Level Features
Pose Filter-Based Ensemble Learning Enables Discovery of Orally Active, Nonsteroidal Farnesoid X Receptor Agonists
Identification and Characterization of an Intermediate Taxol Binding Site Within Microtubule Nanopores and a Mechanism for Tubulin Isotype Binding Selectivity
A database and retrieval system for the NBS tables of chemical thermodynamic properties
WordStar Professional 4
Effect of Anomers and Glycosidic Linkages on the Thermodynamics of Mechanically Stretched Oligosaccharides
Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction
Ligand Pose Predictions for Human G Protein-Coupled Receptors: Insights from the Amber-Based Hybrid Molecular Mechanics/Coarse-Grained Approach
Topological Stabilization of Fullerenes
Demonstration of High-Throughput Building Block and Composition Analysis of Metal-Organic Frameworks
Molecular Mechanics across Chemistry. By Anthony K. Rappé and Carla J. Casewit. University Science Books: Sausalito, California 1997, 444 pp. ISBN 0-935702-77-6
Accurate and Interpretable Computational Modeling of Chemical Mutagenicity
Flexibility and Explicit Solvent in Molecular-Dynamics-Based Docking of Protein-Glycosaminoglycan Systems
Identification of Potent and Selective Acetylcholinesterase/Butyrylcholinesterase Inhibitors by Virtual Screening
Reply to: Limitations in odour recognition and generalization in a neuromorphic olfactory circuit
Automated causal inference in application to randomized controlled clinical trials
Technology can't fix this
The evolution of citation graphs in artificial intelligence research
Reusability report: Annotating metabolite mass spectra with domain-inspired chemical formula transformers
Reusability report: Capturing properties of biological objects and their relationships using graph neural networks
Improving performance of deep learning models with axiomatic attribution priors and expected gradients
Author Correction: Integrated structure prediction of protein-protein docking with experimental restraints using ColabDock
Human-behaviour-based social locomotion model improves the humanization of social robots
Combinatorial optimization with physics-inspired graph neural networks
Learning from models beyond fine-tuning
Shielding sensitive medical imaging data
Strategies needed to counter potential AI misuse
Physical human-robot interaction for clinical care in infectious environments
Developing robust benchmarks for driving forward AI innovation in healthcare
General-purpose foundation models for increased autonomy in robot-assisted surgery
Human-level recognition of blast cells in acute myeloid leukaemia with convolutional neural networks
Moving beyond reward prediction errors
Towards algorithmic analytics for large-scale datasets
Interpretability of artificial neural network models in artificial intelligence versus neuroscience
Publisher Correction: Back to the future with machine learning
Secure, privacy-preserving and federated machine learning in medical imaging
A machine learning platform to estimate anti-SARS-CoV-2 activities
A geometric deep learning approach to predict binding conformations of bioactive molecules
Estimation of continuous valence and arousal levels from faces in naturalistic conditions
Artificial intelligence tackles the nature-nurture debate
Learning motif-based graphs for drug-drug interaction prediction via local-global self-attention
Reusability report: Unpaired deep-learning approaches for holographic image reconstruction
Combining views for newly sequenced organisms
A disease-specific language model for variant pathogenicity in cardiac and regulatory genomics
Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data
Physicochemical graph neural network for learning protein-ligand interaction fingerprints from sequence data
Advanced AI assistants that act on our behalf may not be ethically or legally feasible
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin
Resolution enhancement with a task-assisted GAN to guide optical nanoscopy image analysis and acquisition
Predicting drug-protein interaction using quasi-visual question answering system
Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Speeding up machine hearing
Mind and machine in drug design
End-to-end privacy preserving deep learning on multi-institutional medical imaging
Predicting ultrafast nonlinear dynamics in fibre optics with a recurrent neural network
Author Correction: Predicting equilibrium distributions for molecular systems with deep learning
Neuromorphic visual scene understanding with resonator networks
Data-driven design of soft sensors
A taxonomy and review of generalization research in NLP
Transformers for future medicinal chemists
Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks
Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI
Advances, challenges and opportunities in creating data for trustworthy AI
Personalized deep learning of individual immunopeptidomes to identify neoantigens for cancer vaccines
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data
The rewards of reusable machine learning code
Reply to: The pitfalls of negative data bias for the T-cell epitope specificity challenge
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks
Leveraging language model for advanced multiproperty molecular optimization via prompt engineering
Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion
Connecting the dots in high-energy physics
How to be responsible in AI publication
Predicting the prevalence of complex genetic diseases from individual genotype profiles using capsule networks
Extraction of protein dynamics information from cryo-EM maps using deep learning
A predictive machine learning force-field framework for liquid electrolyte development
A deep learning framework for drug repurposing via emulating clinical trials on real-world patient data
An automated framework for efficiently designing deep convolutional neural networks in genomics
Training deep neural networks for binary communication with the Whetstone method
Segmentation of neurons from fluorescence calcium recordings beyond real time
Deep learning of circulating tumour cells
Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning
Shared human-robot proportional control of a dexterous myoelectric prosthesis
Zero-shot transfer of protein sequence likelihood models to thermostability prediction
When causal inference meets deep learning
Annotating metabolite mass spectra with domain-inspired chemical formula transformers
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics
Geometric deep learning reveals the spatiotemporal features of microscopic motion
Sharing high expectations
A cautionary tale from the machine scientist
Seeking clarity rather than strong opinions on intelligence
AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy
Bridging the neutralization gap for unseen antibodies
The big question
Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks
Mixed-modality speech recognition and interaction using a wearable artificial throat
Machine learning for micro- and nanorobots
A galaxy of data challenges
Feedback GAN for DNA optimizes protein functions
AI minds need to think about energy constraints
Continual learning of context-dependent processing in neural networks
Deep learning at the forefront of detecting tipping points
Automated de novo molecular design by hybrid machine intelligence and rule-driven chemical synthesis
Queering machines
The dangers of using proprietary LLMs for research
Crowdsourcing to predict RNA degradation and secondary structure
AI reflections in 2021
Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning
Discovering fully semantic representations via centroid- and orientation-aware feature learning
Generalizing universal function approximators
Large language models that replace human participants can harmfully misportray and flatten identity groups
Chemical language models enable navigation in sparsely populated chemical space
The challenges of deploying artificial intelligence models in a rapidly evolving pandemic
Artificial microtubules for rapid and collective transport of magnetic microcargoes
How to break information cocoons
Benchmarks for progress in neuromorphic computing
Translating intersectionality to fair machine learning in health sciences
Governing AI safety through independent audits
Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks
Personalized uncertainty quantification in artificial intelligence
Cross-validation is safe to use
Towards quantum enhanced adversarial robustness in machine learning
Generalized radiograph representation learning via cross-supervision between images and free-text radiology reports
Assessing the importance of magnetic resonance contrasts using collaborative generative adversarial networks
A machine learning approach to leveraging electronic health records for enhanced omics analysis
Developing moral AI to support decision-making about antimicrobial use
Developing the knowledge of number digits in a child-like robot
New deepfake regulations in China are a tool for social stability, but at what cost?
Tackling the perils of dual use in AI
A probabilistic challenge for object detection
Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence
Reply to: LncADeep performance on full-length transcripts
From clockwork automata to robot newsreaders
Large language models for scientific discovery in molecular property prediction
The graph connection
Does it matter if empathic AI has no empathy?
Learning characteristics of graph neural networks predicting protein-ligand affinities
Multi-modal molecule structure-text model for text-based retrieval and editing
Exploring scalable medical image encoders beyond text supervision
Regression Transformer enables concurrent sequence regression and generation for molecular language modelling
Tracking the debate on COVID-19 surveillance tools
Unsupervised learning of topological non-Abelian braiding in non-Hermitian bands
Preserving and combining knowledge in robotic lifelong reinforcement learning
Author Correction: Evaluation of deep learning in non-coding RNA classification
Reusability report: Comparing gradient descent and Monte Carlo tree search optimization of quantum annealing schedules
Protein function prediction is improved by creating synthetic feature samples with generative adversarial networks
Solving the Rubik's cube with deep reinforcement learning and search
Memetic robots
Multimodal language and graph learning of adsorption configuration in catalysis
Simple nearest-neighbour analysis meets the accuracy of compound potency predictions using complex machine learning models
Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments
A unified deep framework for peptide-major histocompatibility complex-T cell receptor binding prediction
Active learning for optimal intervention design in causal models
Large-scale chemical language representations capture molecular structure and properties
Hybrid hierarchical learning for solving complex sequential tasks using the robotic manipulation network ROMAN
High-accuracy prostate cancer pathology using deep learning
Contrastive learning enables rapid mapping to multimodal single-cell atlas of multimillion scale
Learning high-level visual representations from a child's perspective without strong inductive biases
Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models
A social network for AI
Reinforcement learning in artificial and biological systems
Testing the limits of natural language models for predicting human language judgements
The AI writing on the wall
Establishing the rules for building trustworthy AI
LncADeep performance on full-length transcripts
Deep learning optoacoustic tomography with sparse data
Generative molecular design in low data regimes
Connecting molecular properties with plain language
Machine learning for data-centric epidemic forecasting
Updating the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) for reporting AI research
Robot planning with LLMs
An interpretable deep learning framework for genome-informed precision oncology
Navigating the development challenges in creating complex data systems
Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis
Publisher Correction: A neural machine code and programming framework for the reservoir computer