AIMC Topic: Databases, Chemical

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Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning.

Database : the journal of biological databases and curation
Medicinal chemistry patents contain rich information about chemical compounds. Although much effort has been devoted to extracting chemical entities from scientific literature, limited numbers of patent mining systems are publically available, probab...

PCOSKB: A KnowledgeBase on genes, diseases, ontology terms and biochemical pathways associated with PolyCystic Ovary Syndrome.

Nucleic acids research
Polycystic ovary syndrome (PCOS) is one of the major causes of female subfertility worldwide and ≈ 7-10% of women in reproductive age are affected by it. The affected individuals exhibit varying types and levels of comorbid conditions, along with the...

Highly predictive support vector machine (SVM) models for anthrax toxin lethal factor (LF) inhibitors.

Journal of molecular graphics & modelling
Anthrax is a highly lethal, acute infectious disease caused by the rod-shaped, Gram-positive bacterium Bacillus anthracis. The anthrax toxin lethal factor (LF), a zinc metalloprotease secreted by the bacilli, plays a key role in anthrax pathogenesis ...

Predicting Melting Points of Organic Molecules: Applications to Aqueous Solubility Prediction Using the General Solubility Equation.

Molecular informatics
In this work we make predictions of several important molecular properties of academic and industrial importance to seek answers to two questions: 1) Can we apply efficient machine learning techniques, using inexpensive descriptors, to predict meltin...

Quantitative Regression Models for the Prediction of Chemical Properties by an Efficient Workflow.

Molecular informatics
Rapid safety assessment is more and more needed for the increasing chemicals both in chemical industries and regulators around the world. The traditional experimental methods couldn't meet the current demand any more. With the development of the info...

BiNChE: a web tool and library for chemical enrichment analysis based on the ChEBI ontology.

BMC bioinformatics
BACKGROUND: Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biol...

Determination of Meta-Parameters for Support Vector Machine Linear Combinations.

Molecular informatics
Support vector machines (SVMs) are among the most popular machine learning methods for compound classification and other chemoinformatics tasks such as, for example, the prediction of ligand-target pairs or compound activity profiles. Depending on th...

GTM-Based QSAR Models and Their Applicability Domains.

Molecular informatics
In this paper we demonstrate that Generative Topographic Mapping (GTM), a machine learning method traditionally used for data visualisation, can be efficiently applied to QSAR modelling using probability distribution functions (PDF) computed in the l...

Three- and four-class classification models for P-glycoprotein inhibitors using counter-propagation neural networks.

SAR and QSAR in environmental research
P-glycoprotein (P-gp) is an ATP binding cassette (ABC) transporter that helps to protect several certain human organs from xenobiotic exposure. This efflux pump is also responsible for multi-drug resistance (MDR), an issue of the chemotherapy approac...

Development of a novel fingerprint for chemical reactions and its application to large-scale reaction classification and similarity.

Journal of chemical information and modeling
Fingerprint methods applied to molecules have proven to be useful for similarity determination and as inputs to machine-learning models. Here, we present the development of a new fingerprint for chemical reactions and validate its usefulness in build...