NDLI: Supervised learning with decision tree-based methods in computational and systems biology

Please wait, while we are loading the content...

Amidoligases with ATP-grasp, glutamine synthetase-like and acetyltransferase-like domains: synthesis of novel metabolites and peptide modifications of proteins

Integration of signals from the B-cell antigen receptor and the IL-4 receptor leads to a cooperative shift in the cellular response axis

Predicting essential genes based on network and sequence analysis

Coding DNA repeated throughout intergenic regions of the Arabidopsis thaliana genome: evolutionary footprints of RNA silencing

Analysis of structured and intrinsically disordered regions of transmembrane proteins

Genome-wide analysis predicts DNA structural motifs as nucleosome exclusion signals

Stable G-quadruplexes are found outside nucleosome-bound regions

A dependency graph approach for the analysis of differential gene expression profiles

A network-based method for predicting gene–nutrient interactions and its application to yeast amino-acid metabolism

Strategies for efficient disruption of metabolism in Mycobacterium tuberculosis from network analysis

Unraveling the potential of intrinsically disordered proteins as drug targets: application to Mycobacterium tuberculosis

Relative stability of DNA as a generic criterion for promoter prediction: whole genome annotation of microbial genomes with varying nucleotide base composition

Towards inferring time dimensionality in protein–protein interaction networks by integrating structures: the p53 example

Energy based approach for understanding the recognition mechanism in protein–protein complexes

Modular logical modelling of the budding yeast cell cycle

Dissection of USP catalytic domains reveals five common insertion points

Signaling network analysis of ubiquitin-mediated proteins suggests correlations between the 26S proteasome and tumor progression

Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development

A c-Myc regulatory subnetwork from human transposable element sequences

Inferring the transcriptional network of Bacillus subtilis

Signal amplification in a lattice of coupled protein kinases

Ligand dependent intra and inter subunit communication in human tryptophanyl tRNA synthetase as deduced from the dynamics of structure networks

Correlation between mRNA expression levels and protein aggregation propensities in subcellular localisations

Molecular modeling and docking studies of human 5-hydroxytryptamine 2A (5-HT_2A) receptor for the identification of hotspots for ligand binding

An integrative approach towards completing genome-scale metabolic networks

DNA supercoiling regulates the stress-inducible expression of genes in the cyanobacterium Synechocystis

A metabolomic and multivariate statistical process to assess the effects of genotoxins in Saccharomycescerevisiae

The ABC of reverse engineering biological signalling systems

Prediction of conditional gene essentiality through graph theoretical analysis of genome-wide functional linkages

A global view of Escherichia coli Rsd protein and its interactions

Back matter

Back cover

Molecular BioSystems Vol - 5 Issue - 9

Molecular BioSystems Vol - 5 Issue - 8

Molecular BioSystems Vol - 5 Issue - 7

Molecular BioSystems Vol - 5 Issue - 6

Molecular BioSystems Vol - 5 Issue - 5

Molecular BioSystems Vol - 5 Issue - 4

Molecular BioSystems Vol - 5 Issue - 3

Molecular BioSystems Vol - 5 Issue - 2

Molecular BioSystems Vol -4

Molecular BioSystems Vol -3

Molecular BioSystems Vol -2

Supervised learning with decision tree-based methods in computational and systems biology

Content Provider	Royal Society of Chemistry (RSC)
Author	Geurts, Pierre Wehenkel, Louis Irrthum, Alexandre
Copyright Year	2009
Abstract	At the intersection between artificial intelligence and statistics, supervised learning allows algorithms to automatically build predictive models from just observations of a system. During the last twenty years, supervised learning has been a tool of choice to analyze the always increasing and complexifying data generated in the context of molecular biology, with successful applications in genome annotation, function prediction, or biomarker discovery. Among supervised learning methods, decision tree-based methods stand out as non parametric methods that have the unique feature of combining interpretability, efficiency, and, when used in ensembles of trees, excellent accuracy. The goal of this paper is to provide an accessible and comprehensive introduction to this class of methods. The first part of the review is devoted to an intuitive but complete description of decision tree-based methods and a discussion of their strengths and limitations with respect to other supervised learning methods. The second part of the review provides a survey of their applications in the context of computational and systems biology.
Starting Page	1593
Ending Page	1605
Page Count	13
File Format	HTM / HTML PDF
ISSN	1742206X
Volume Number	5
Issue Number	12
Journal	Molecular BioSystems
DOI	10.1039/b907946g
Language	English
Publisher	Royal Society of Chemistry
Access Restriction	Open
Subject Keyword	Biomarker Supervised learning Systems biology Machine learning Artificial intelligence DNA annotation Computational biology
Content Type	Text
Resource Type	Article
Subject	Molecular Biology Biotechnology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Semi-supervised self-training for decision tree classifiers

A new decision-tree classification algorithm for machine learning

Classifying pairs with trees for supervised biological network inference.

Automatic image annotation based on decision tree machine learning

Comprehensive study of semi-supervised learning for DNA methylation-based supervised classification of central nervous system tumors

Recent advances in system management, decision support systems, artificial intelligence and computing in anaesthesia.

Induction Tree methods to classify M. tuberculosis spoligotypes

An Improved Perceptron Tree Learning Model Based Intrusion Detection Approach

Semi-supervised self-training for decision tree classifiers

Supervised learning with decision tree-based methods in computational and systems biology

Similar Documents

Semi-supervised self-training for decision tree classifiers

A new decision-tree classification algorithm for machine learning

Classifying pairs with trees for supervised biological network inference.

Automatic image annotation based on decision tree machine learning

Comprehensive study of semi-supervised learning for DNA methylation-based supervised classification of central nervous system tumors

Recent advances in system management, decision support systems, artificial intelligence and computing in anaesthesia.

Induction Tree methods to classify M. tuberculosis spoligotypes

An Improved Perceptron Tree Learning Model Based Intrusion Detection Approach

Semi-supervised self-training for decision tree classifiers

Supervised learning with decision tree-based methods in computational and systems biology