Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Videos

Applying data mining techniques to library design, lead generation and lead optimization.

Daniel C Weaver¹

¹Array Biopharma, Inc., 3200 Walnut Street, Boulder, Colorado 80303, USA. dweaver@arraybiopharma.com

Current Opinion in Chemical Biology

|June 9, 2004

Summary

This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Plasma proteome of growing tumors.

Scientific reports·2023

Same author

Relationships between Prediction Accuracy, Metacognitive Reflection, and Performance in Introductory Genetics Students.

CBE life sciences education·2022

Same journal

Function through shape: An overview of DNA G-quadruplexes in transcriptional regulation.

Current opinion in chemical biology·2026

Same journal

Advances in tools and technologies for multiplexed bioluminescence imaging.

Current opinion in chemical biology·2026

Same journal

High-resolution molecular mapping by expansion-coupled label-free and multimodal imaging.

Current opinion in chemical biology·2026

Same journal

Recent advances in glycoconjugate-based therapeutics.

Current opinion in chemical biology·2026

Same journal

Towards better red emitters for bioimaging: Innovations in rhodamine and cyanine chemistry.

Current opinion in chemical biology·2026

Same journal

Chemigenetic fluorescent biosensors in biological imaging - New trends and advances.

Current opinion in chemical biology·2026

See all related articles

This review explores data mining for drug discovery, focusing on its use in designing new compound libraries and optimizing drug leads. It highlights patterns in quantitative structure-activity relationship (QSAR) modeling and comparative studies of various data mining techniques.

Area of Science:

Computational chemistry and cheminformatics
Pharmacology and drug discovery

Background:

Data mining techniques are increasingly applied to chemical and biological datasets.
These methods aid in understanding structure-activity relationships and designing novel molecular libraries.

Purpose of the Study:

To review data mining concepts and their applications in drug discovery.
To discuss library design, lead generation, and lead optimization using data mining.
To summarize comparative studies and emerging trends in the field.

Main Methods:

Review of existing literature on data mining applications in drug discovery.
Analysis of quantitative structure-activity relationship (QSAR) model generation and interpretation.
Discussion of comparative studies evaluating different data mining algorithms.

Related Experiment Videos

Main Results:

Data mining models are valuable tools for understanding structure-activity relationships.
Techniques effectively support library design, lead generation, and optimization.
Emerging patterns in drug discovery data mining are identified through comparative analyses.

Conclusions:

Data mining offers powerful approaches for accelerating drug discovery processes.
Understanding QSAR models is crucial for rational drug design.
Continued comparative studies will refine the application of data mining in pharmaceutical research.