Editorial: Charting Chemical Space: Challenges and Opportunities for Artificial Intelligence and Machine Learning.

scientific article published in September 2011

Editorial: Charting Chemical Space: Challenges and Opportunities for Artificial Intelligence and Machine Learning. is …
instance of (P31):
editorialQ871232
scholarly articleQ13442814

External links are
P356DOI10.1002/MINF.201180003
P698PubMed publication ID27467407
P5875ResearchGate publication ID264299135

P50authorPierre BaldiQ3383843
Klaus-Robert MüllerQ26709023
Gisbert SchneiderQ51615601
P2860cites workGrand challenges for cheminformaticsQ21198770
Virtual screening: an endless staircase?Q28278411
Tree and Hashing Data Structures to Speed up Chemical Searches: Analysis and ExperimentsQ31118070
Chemoinformatics as a Theoretical Chemistry DisciplineQ38911197
Probabilistic Substructure Mining From Small-Molecule ScreensQ39550751
Modeling Choices for Virtual Screening Hit IdentificationQ39550763
From Hits to Leads: Challenges for the Next Phase of Machine Learning in Medicinal Chemistry.Q45961575
SketchSort: Fast All Pairs Similarity Search for Large Databases of Molecular FingerprintsQ48056211
Visual Interpretation of Kernel-Based Prediction Models.Q51536156
Target-Driven Subspace Mapping Methods and Their Applicability Domain EstimationQ88013592
P433issue9
P921main subjectmachine learningQ2539
artificial intelligenceQ11660
P304page(s)751
P577publication date2011-09-01
P1433published inMolecular InformaticsQ3319476
P1476titleEditorial: Charting Chemical Space: Challenges and Opportunities for Artificial Intelligence and Machine Learning.
P478volume30

Reverse relations

cites work (P2860)
Q45945301Empirical Classification of Trajectory Data: An Opportunity for the Use of Machine Learning in Molecular Dynamics.
Q45943212Quantum machine learning in chemical compound space.

Search more.