WO2010060746A3 - Method and device for the automatic analysis of models - Google Patents

Method and device for the automatic analysis of models Download PDF

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Publication number
WO2010060746A3
WO2010060746A3 PCT/EP2009/064476 EP2009064476W WO2010060746A3 WO 2010060746 A3 WO2010060746 A3 WO 2010060746A3 EP 2009064476 W EP2009064476 W EP 2009064476W WO 2010060746 A3 WO2010060746 A3 WO 2010060746A3
Authority
WO
WIPO (PCT)
Prior art keywords
linear model
automatic analysis
training
models
measure
Prior art date
Application number
PCT/EP2009/064476
Other languages
German (de)
French (fr)
Other versions
WO2010060746A2 (en
Inventor
Klaus-Robert MÜLLER
Timon Schroeter
Katja Hansen
Original Assignee
Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
Technische Universität Berlin
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V., Technische Universität Berlin filed Critical Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
Priority to DE112009002693T priority Critical patent/DE112009002693A5/en
Publication of WO2010060746A2 publication Critical patent/WO2010060746A2/en
Publication of WO2010060746A3 publication Critical patent/WO2010060746A3/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/70—Machine learning, data mining or chemometrics
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/30—Prediction of properties of chemical compounds, compositions or mixtures
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
    • G16C20/80—Data visualisation

Abstract

The invention relates to a method and a device for the automatic analysis of a non-linear model for predicting the properties of an object which is a priori not characterized. According to the method, a) the non-linear model is elaborated for training objects based on a mechanical learning method, especially a kernel-based learning method, in such a manner that it allows a statement regarding at least one property for at least one object, b) at least one measure is automatically determined by means of an analytical element using the representer theorem, said measure indicating which training object or which training objects that have become part of the non-linear model have the strongest influence on the predictions of the non-linear model, and c) a prioritized data set is automatically produced in which the measures of the influencing factors are put in the order of a predetermined condition.
PCT/EP2009/064476 2008-11-26 2009-11-02 Method and device for the automatic analysis of models WO2010060746A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
DE112009002693T DE112009002693A5 (en) 2008-11-26 2009-11-02 Method and device for automatic analysis of models

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102008059045 2008-11-26
DE102008059045.2 2008-11-26

Publications (2)

Publication Number Publication Date
WO2010060746A2 WO2010060746A2 (en) 2010-06-03
WO2010060746A3 true WO2010060746A3 (en) 2010-11-18

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2009/064476 WO2010060746A2 (en) 2008-11-26 2009-11-02 Method and device for the automatic analysis of models

Country Status (2)

Country Link
DE (1) DE112009002693A5 (en)
WO (1) WO2010060746A2 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10036219B1 (en) 2017-02-01 2018-07-31 Chevron U.S.A. Inc. Systems and methods for well control using pressure prediction

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001031580A2 (en) * 1999-10-27 2001-05-03 Biowulf Technologies, Llc Methods and devices for identifying patterns in biological systems
WO2007031716A1 (en) * 2005-09-13 2007-03-22 Imperial Innovations Limited Support vector inductive logic programming

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001031580A2 (en) * 1999-10-27 2001-05-03 Biowulf Technologies, Llc Methods and devices for identifying patterns in biological systems
WO2007031716A1 (en) * 2005-09-13 2007-03-22 Imperial Innovations Limited Support vector inductive logic programming

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
A. SCHWAIGHOFER ET AL.: "A Probabilistic Approach to Classifying Metabolic Stability", J. CHEM. INF. MODEL., vol. 48, no. 4, 8 March 2008 (2008-03-08), pages 785 - 796, XP002592596, Retrieved from the Internet <URL:http://pubs.acs.org/doi/pdf/10.1021/ci700142c> [retrieved on 20100720], DOI: 10.1021/ci700142c *
JORISSEN ROBERT N ET AL: "Virtual screening of molecular databases using a support vector machine", JOURNAL OF CHEMICAL INFORMATION AND MODELING, vol. 45, no. 3, 1 May 2005 (2005-05-01), AMERICAN CHEMICAL SOCIETY, WASHINGTON, DC, US, pages 549 - 561, XP002520927, ISSN: 1549-9596, [retrieved on 20050416], DOI: 10.1021/cI049641u *
KURT DRIESSENS ET AL: "Graph kernels and Gaussian processes for relational reinforcement learning", MACHINE LEARNING, vol. 64, no. 1-3, 8 May 2006 (2006-05-08), KLUWER ACADEMIC PUBLISHERS-PLENUM PUBLISHERS, pages 91 - 119, XP019403046, ISSN: 1573-0565, DOI: 10.1007/s10994-006-8258-y *
RALAIVOLA L ET AL: "Graph kernels for chemical informatics", NEURAL NETWORKS, vol. 18, no. 8, 1 October 2005 (2005-10-01), ELSEVIER SCIENCE PUBLISHERS, pages 1093 - 1110, XP025334096, ISSN: 0893-6080, [retrieved on 20051001] *
TIMON SEBASTIAN SCHROETER ET AL: "Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules", JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, vol. 21, no. 12, 1 December 2007 (2007-12-01), KLUWER ACADEMIC PUBLISHERS, pages 651 - 664, XP019574628, ISSN: 1573-4951 *
WEI CHU, S. SATHIYA KEERTHI, CHONG JIN ONG AND ZOUBIN GHAHRAMANI: "Bayesian support vector machines for feature ranking and selection", FEATURE EXTRACTION, FOUNDATIONS AND APPLICATIONS, 2006, pages 1 - 16, XP002592595, Retrieved from the Internet <URL:http://www.gatsby.ucl.ac.uk/%7Echuwei/paper/fsc04.pdf> [retrieved on 20100720] *

Also Published As

Publication number Publication date
WO2010060746A2 (en) 2010-06-03
DE112009002693A5 (en) 2013-01-10

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