This paper introduces DynamicFlow, a full-atom stochastic flow matching model that simultaneously generates ligand molecules and transforms protein pockets from apo to holo states. It also contributes a new dataset of MD-simulated apo-holo pairs derived from MISATO.
InvMSAFold replaces autoregressive decoding with a Potts model parameter generator, enabling diverse protein sequence sampling orders of magnitude faster than ESM-IF1.
A three-level grammatical framework (formula, molecule, text) for parsing online handwritten chemical formulas, generating semantic graphs that capture both connectivity and layout using context-free grammars and HMMs.
This paper proposes a double-stage architecture using SVM for rough classification and HMM for fine recognition. It features a novel Point Sequence Reordering (PSR) algorithm that significantly improves accuracy on organic ring structures.
Proposes a unified statistical framework for recognizing both inorganic and organic handwritten chemical expressions. Introduces the Chemical Expression Structure Graph (CESG) and uses a weighted direction graph search for structural analysis, achieving 83.1% top-5 accuracy on a large proprietary dataset.
Describes chemoCR, a system that converts bitmap chemical diagrams into connection tables using a pipeline of texture-based vectorization, OCR, and a rule-based expert system, achieving 65.6% perfect recall on the TREC 2011 task.
ChemInk introduces a sketch recognition system for chemical diagrams that combines multi-level visual features via a joint Conditional Random Field (CRF), achieving 97.4% accuracy and outperforming CAD tools in user speed.
This paper introduces CLiDE Pro, an advanced OCSR system that segments document images and reconstructs chemical connection tables. It features novel handling for crossing bonds and generic structures, validating performance on a publicly released benchmark of 454 scanned images.
Imago is an open-source, cross-platform C++ toolkit designed to recognize 2D chemical structure images from scientific papers and convert them into machine-readable molecule formats using a rule-based pipeline.
This paper proposes a strategy for interpreting handwritten chemical formulas by converting bitmap images into a dynamic structural graph of quadrilaterals. It achieves ~97% recognition on graphical elements by using recursive ‘specialists’ to identify chemical bonds and rings.
This paper introduces NOMINATE, a probabilistic spatial model that recovers metric coordinates for legislators and roll calls from nominal voting data, demonstrating that a single liberal-conservative dimension explains the vast majority of Congressional voting behavior.
This methodological paper presents a system for digitizing chemical images into SDF files. It utilizes a custom vectorization algorithm and chemical rule validation, achieving 94% accuracy on benchmark datasets compared to 50% for commercial tools.