NDLI: Tissue classification with gene expression profiles

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

On approximation algorithms for local multiple alignment

Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function

A combinatorial approach to protein docking with flexible side-chains

Optimal amnesic probabilistic automata or how to learn and classify proteins in linear time and space

The NOESY jigsaw: automated protein secondary structure and main-chain assignment from sparse, unassigned NMR data

Sequencing a genome by walking with clone-end sequences (abstract): a mathematical analysis

Human and mouse gene structure: comparative analysis and application to exon prediction

Tissue classification with gene expression profiles

Universal DNA tag systems: a combinatorial design scheme

Comprehensive statistical method for protein fold recognition

An analytic approach to significance assessment in local sequence alignment with gaps

Notung: dating gene duplications using gene family trees

A compression algorithm for DNA sequences and its applications in genome comparison

Multiple maxima of likelihood in phylogenetic trees: an analytic approach

Compuational analyses of developmental cis-regualtory control systems (invited presentation)

Tree fitting: an algebraic approach using profile distances

Using Bayesian networks to analyze expression data

Invited presentation: introns and modules in ancient conserved genes (abstract only)

Evolutionary features of genomes as disclosed by comparative analysis of complete genome sequences (abstract only)

New algorithms for the duplication-loss model

Systematic and automated discovery of patterns in PROSITE families

Contig selection in physical mapping

A data-analysis pipeline for large-scale gene expression analysis

Computing life and global technologies (abstract only)

DNA sequence variation among humans and apes (abstract only)

Sequence comparison to graph comparison—a new generation of algorithms for network analysis of interacting molecules (abstract only)

Optimizing for success: a new score function for distantly related protein sequence comparison

Reconstructing distances in physical maps of chromosomes with nonoverlapping probes

UNRES: a united-residue force field for energy-based prediction of protein structure—orgin and significance of multibody terms

Pseudoknots in RNA secondary structures

Extracting structured motifs using a suffix tree—algorithms and application to promoter consensus identification

Molecular diversity (abstract only): strategies and concerns

Human genome analysis and medicine in the 21st century (abstract only)

Determining contact energy function for continuous state models of globular protein conformations

Mutation-tolerant protein identification by mass-spectrometry

Probabilities for having a new fold on the basis of a map of all protein sequences

Sequencing-by-hybridization at the information-theory bound: an optimal algorithm

Early eukaryote evolution based on mitochondrial gene order breakpoints

Class prediction and discovery using gene expression data

Matching simulation and experiment (extended abstract): a new simplified model for simulating protein folding

PDB_ISL: an intermediate sequence library for protein structure assignment

The E-CELL project: towards integrative simulation of cellular processes

Protein structure determination using protein threading and sparse NMR data (extended abstract)

A unified sequence-structure classification of protein sequences: combining sequence and structure in a map of the protein space

A simple iterative approach to parameter optimization

Tissue classification with gene expression profiles

Content Provider	ACM Digital Library
Author	Yakhini, Zohar Friedman, Nir Ben-Dor, Amir Nachman, Iftach Schummer, Michèl Bruhn, Laurakay
Abstract	Constantly improving gene expression profiling technologies are expected to provide understanding and insight into cancer related cellular processes. Gene expression data is also expected to significantly and in the development of efficient cancer diagnosis and classification platforms. In this work we examine two sets of gene expression data measured across sets of tumor and normal clinical samples One set consists of 2,000 genes, measured in 62 epithelial colon samples [1]. The second consists of ≈ 100,000 clones, measured in 32 ovarian samples (unpublished, extension of data set described in [26]).We examine the use of scoring methods, measuring separation of tumors from normals using individual gene expression levels. These are then coupled with high dimensional classification methods to assess the classification power of complete expression profiles. We present results of performing leave-one-out cross validation (LOOCV) experiments on the two data sets. employing SVM [8], AdaBoost [13] and a novel clustering based classification technique. As tumor samples can differ from normal samples in their cell-type composition we also perform LOOCV experiments using appropriately modified sets of genes, attempting to eliminate the resulting bias.We demonstrate success rate of at least 90% in tumor vs normal classification, using sets of selected genes, with as well as without cellular contamination related members. These results are insensitive to the exact selection mechanism, over a certain range.
Starting Page	54
Ending Page	64
Page Count	11
File Format	PDF
ISBN	1581131860
DOI	10.1145/332306.332328
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2000-04-08
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

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