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Stereo Signature Molecular Descriptor

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/1521-3765(20010917)7:18<3985::aid-chem3985>3.0.co;2-0openalex-snapshot
Cahn-Ingold-Prelog Descriptors of Absolute Configuration for Carbon Cages
inferredcites →https://doi.org/10.1007/978-1-4684-2001-2_13openalex-snapshot
Isomorphism of Planar Graphs (Working Paper)
inferredcites →https://doi.org/10.1016/0021-9673(95)00401-7openalex-snapshot
Use of topological descriptiors in chromatographic chiral separations
inferredcites →https://doi.org/10.1016/j.bmcl.2012.10.102openalex-snapshot
QSAR investigation of NaV1.7 active compounds using the SVM/Signature approach and the Bioclipse Modeling platform
inferredcites →https://doi.org/10.1016/j.jmgm.2003.10.002openalex-snapshot
The signature molecular descriptor
inferredcites →https://doi.org/10.1021/ci020345wopenalex-snapshot
The Signature Molecular Descriptor. 1. Using Extended Valence Sequences in QSAR and QSPR Studies
inferredcites →https://doi.org/10.1021/ci025516bopenalex-snapshot
QSAR Modeling Using Chirality Descriptors Derived from Molecular Topology
inferredcites →https://doi.org/10.1021/ci0341823openalex-snapshot
The Signature Molecular Descriptor. 4. Canonizing Molecules Using Extended Valence Sequences
inferredcites →https://doi.org/10.1021/ci0499469openalex-snapshot
Development of QSAR Models To Predict and Interpret the Biological Activity of Artemisinin Analogues
inferredcites →https://doi.org/10.1021/ci600235wopenalex-snapshot
Physicochemical Stereodescriptors of Atomic Chiral Centers
inferredcites →https://doi.org/10.1021/ci600238jopenalex-snapshot
Algorithm for Advanced Canonical Coding of Planar Chemical Structures That Considers Stereochemical and Symmetric Information
inferredcites →https://doi.org/10.1021/ci9002206openalex-snapshot
Interpretation of Nonlinear QSAR Models Applied to Ames Mutagenicity Data
inferredcites →https://doi.org/10.1021/ja00226a005openalex-snapshot
Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins
inferredcites →https://doi.org/10.1023/a:1008052320014openalex-snapshot
An extensive ecdysteroid CoMFA
inferredcites →https://doi.org/10.1093/bioinformatics/btm580openalex-snapshot
Genome scale enzyme–metabolite and drug–target interaction predictions using the signature molecular descriptor
inferredcites →https://doi.org/10.1093/bioinformatics/btq317openalex-snapshot
Molecular signatures-based prediction of enzyme promiscuity
inferredcites →https://doi.org/10.1093/nar/gkm882openalex-snapshot
KEGG for linking genomes to life and the environment
inferredcites →https://doi.org/10.1093/nar/gkq1126openalex-snapshot
DrugBank 3.0: a comprehensive resource for 'Omics' research on drugs
inferredcites →https://doi.org/10.1145/1961189.1961199openalex-snapshot
LIBSVM
inferredcites →https://doi.org/10.1201/9781420082999-c11openalex-snapshot
Reaction Network Generation
inferredcites →https://doi.org/10.1360/jos180001openalex-snapshot
A Time Petri Net Extended with Price Information
inferredcites →https://doi.org/10.18637/jss.v011.i09openalex-snapshot
kernlab - An S4 Package for Kernel Methods in R
inferredcites →https://doi.org/10.18637/jss.v018.i02openalex-snapshot
The pls Package: Principal Component and Partial Least Squares Regression in R
inferredcites →https://doi.org/10.18637/jss.v018.i05openalex-snapshot
Chemical Informatics Functionality in R

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Neural‐Symbolic Machine Learning for Retrosynthesis and Reaction Prediction
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Emerging tools, enabling technologies, and future opportunities for the bioproduction of aromatic chemicals
inferred← citeshttps://doi.org/10.1002/minf.202060030openalex-snapshot
Multiple Conformer Descriptors for QSAR Modeling
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Computer Representation of Chemical Compounds
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Sequence Retriever for Known, Discovered, and User-Specified Molecular Fragments
inferred← citeshttps://doi.org/10.1007/978-3-319-56850-8_4openalex-snapshot
Structural, Physicochemical and Stereochemical Interpretation of QSAR Models Based on Simplex Representation of Molecular Structure
inferred← citeshttps://doi.org/10.1007/978-94-007-6169-8_50-1openalex-snapshot
Computer Representation of Chemical Compounds
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Identification of major malate export systems in an engineered malate-producing Escherichia coli aided by substrate similarity search
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Many InChIs and quite some feat
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Computer-Aided Synthesis Planning for Biocatalysis
inferred← citeshttps://doi.org/10.1016/b978-0-444-63683-6.00011-3openalex-snapshot
The Signature Molecular Descriptor in Molecular Design
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Neuropathy target esterase (NTE/PNPLA6) and organophosphorus compound-induced delayed neurotoxicity (OPIDN)
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Reproducing the color with reformulated recipe
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Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry
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Machine learning induction of chemically intuitive rules for the prediction of enantioselectivity in the asymmetric syntheses of alcohols
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Computer-aided design for metabolic engineering
inferred← citeshttps://doi.org/10.1016/j.jmgm.2016.07.008openalex-snapshot
Open source molecular modeling
inferred← citeshttps://doi.org/10.1016/j.jmgm.2019.107479openalex-snapshot
Prediction on separation factor of chiral arylhydantoin compounds and recognition mechanism between chiral stationary phase and the enantiomers
inferred← citeshttps://doi.org/10.1016/j.rechem.2022.100379openalex-snapshot
Machine learnt patterns in rhodium-catalysed asymmetric Michael addition using chiral diene ligands
inferred← citeshttps://doi.org/10.1016/j.ymben.2017.12.002openalex-snapshot
RetroPath2.0: A retrosynthesis workflow for metabolic engineers
inferred← citeshttps://doi.org/10.1021/acs.chemrev.9b00425openalex-snapshot
Quantitative Structure–Selectivity Relationships in Enantioselective Catalysis: Past, Present, and Future
inferred← citeshttps://doi.org/10.1021/acs.est.1c02376openalex-snapshot
Direct Prediction of Bioaccumulation of Organic Contaminants in Plant Roots from Soils with Machine Learning Models Based on Molecular Structures
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00543openalex-snapshot
Get Your Atoms in Order—An Open-Source Implementation of a Novel and Robust Molecular Canonicalization Algorithm
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00159openalex-snapshot
Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets
inferred← citeshttps://doi.org/10.1021/acssynbio.4c00091openalex-snapshot
Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review
inferred← citeshttps://doi.org/10.1021/acssynbio.5b00294openalex-snapshot
Semisupervised Gaussian Process for Automated Enzyme Search
inferred← citeshttps://doi.org/10.1021/sb4001273openalex-snapshot
Retropath: Automated Pipeline for Embedded Metabolic Circuits
inferred← citeshttps://doi.org/10.1038/nrd4128openalex-snapshot
Chemical predictive modelling to improve compound quality
inferred← citeshttps://doi.org/10.1038/s41524-020-00429-wopenalex-snapshot
Machine learning property prediction for organic photovoltaic devices
inferred← citeshttps://doi.org/10.1039/c6cp06380bopenalex-snapshot
A stochastic method for asphaltene structure formulation from experimental data: avoidance of implausible structures
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Advances and perspectives in computer-assisted structure elucidation: a review
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Accelerating the discovery of high-efficiency donor–acceptor pairs in organic photovoltaics via SolarPCE-Net guided screening
inferred← citeshttps://doi.org/10.1093/bioinformatics/btv486openalex-snapshot
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inferred← citeshttps://doi.org/10.1093/nar/gku362openalex-snapshot
XTMS: pathway design in an eXTended metabolic space
inferred← citeshttps://doi.org/10.1093/nar/gkw305openalex-snapshot
SensiPath: computer-aided design of sensing-enabling metabolic pathways
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RetroRules: a database of reaction rules for engineering biology
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Discovery of (meth)acrylate polymers that resist colonization by fungi associated with pathogenesis and biodeterioration
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In Silico Mechanistic Profiling to Probe Small Molecule Binding to Sulfotransferases
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Machine Learning Spectroscopy Based on Group Contribution and Molecule Contribution Methods
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A Universal Framework for General Prediction of Physicochemical Properties: The Natural Growth Model
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Mining conserved neighborhood patterns in metabolic and genomic contexts
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