Online phenotype discovery in high-content RNAi screens using gap statistics

Zheng Yin; Xiaobo Zhou; Chris Bakal; Fuhai Li; Youxian Sun; Norbert Perrimon; Stephen T C Wong

doi:10.1063/1.2816647

Online phenotype discovery in high-content RNAi screens using gap statistics

Zheng Yin, Xiaobo Zhou, Chris Bakal, Fuhai Li, Youxian Sun, Norbert Perrimon, Stephen T C Wong

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Discovering and identifying novel phenotypes from images inputting online is a major challenge in high-content RNA interference (RNAi) screens. Discovered phenotypes should be visually distinct from existing ones and make biological sense. An online phenotype discovery method featuring adaptive phenotype modeling and iterative cluster merging using gap statistics is proposed. The method works well on discovering new phenotypes adaptively when applied to both of synthetic data sets and RNAi high content screen (HCS) images with ground truth labels.

Original language	English (US)
Title of host publication	Computational Models For Life Sciences (CMLS '07) - 2007 International Symposium
Pages	86-95
Number of pages	10
Volume	952
DOIs	https://doi.org/10.1063/1.2816647
State	Published - Dec 1 2007
Event	2007 International Symposium on Computational Models for Life Sciences, CMLS '07 - Gold Coast, QLD, Australia Duration: Dec 17 2007 → Dec 19 2007

Other

Other	2007 International Symposium on Computational Models for Life Sciences, CMLS '07
Country/Territory	Australia
City	Gold Coast, QLD
Period	12/17/07 → 12/19/07

Keywords

Gap statistics
High content screen
Phenotype discovery
RNA interference

ASJC Scopus subject areas

General Physics and Astronomy

Access to Document

10.1063/1.2816647

Cite this

Yin, Z, Zhou, X, Bakal, C, Li, F, Sun, Y, Perrimon, N & Wong, STC 2007, Online phenotype discovery in high-content RNAi screens using gap statistics. in Computational Models For Life Sciences (CMLS '07) - 2007 International Symposium. vol. 952, pp. 86-95, 2007 International Symposium on Computational Models for Life Sciences, CMLS '07, Gold Coast, QLD, Australia, 12/17/07. https://doi.org/10.1063/1.2816647

@inproceedings{e1ee8dd14f88411b9184888de38115c3,

title = "Online phenotype discovery in high-content RNAi screens using gap statistics",

abstract = "Discovering and identifying novel phenotypes from images inputting online is a major challenge in high-content RNA interference (RNAi) screens. Discovered phenotypes should be visually distinct from existing ones and make biological sense. An online phenotype discovery method featuring adaptive phenotype modeling and iterative cluster merging using gap statistics is proposed. The method works well on discovering new phenotypes adaptively when applied to both of synthetic data sets and RNAi high content screen (HCS) images with ground truth labels.",

keywords = "Gap statistics, High content screen, Phenotype discovery, RNA interference",

author = "Zheng Yin and Xiaobo Zhou and Chris Bakal and Fuhai Li and Youxian Sun and Norbert Perrimon and Wong, {Stephen T C}",

year = "2007",

month = dec,

day = "1",

doi = "10.1063/1.2816647",

language = "English (US)",

isbn = "9780735404663",

volume = "952",

pages = "86--95",

booktitle = "Computational Models For Life Sciences (CMLS '07) - 2007 International Symposium",

note = "2007 International Symposium on Computational Models for Life Sciences, CMLS '07 ; Conference date: 17-12-2007 Through 19-12-2007",

}

TY - GEN

T1 - Online phenotype discovery in high-content RNAi screens using gap statistics

AU - Yin, Zheng

AU - Zhou, Xiaobo

AU - Bakal, Chris

AU - Li, Fuhai

AU - Sun, Youxian

AU - Perrimon, Norbert

AU - Wong, Stephen T C

PY - 2007/12/1

Y1 - 2007/12/1

N2 - Discovering and identifying novel phenotypes from images inputting online is a major challenge in high-content RNA interference (RNAi) screens. Discovered phenotypes should be visually distinct from existing ones and make biological sense. An online phenotype discovery method featuring adaptive phenotype modeling and iterative cluster merging using gap statistics is proposed. The method works well on discovering new phenotypes adaptively when applied to both of synthetic data sets and RNAi high content screen (HCS) images with ground truth labels.

AB - Discovering and identifying novel phenotypes from images inputting online is a major challenge in high-content RNA interference (RNAi) screens. Discovered phenotypes should be visually distinct from existing ones and make biological sense. An online phenotype discovery method featuring adaptive phenotype modeling and iterative cluster merging using gap statistics is proposed. The method works well on discovering new phenotypes adaptively when applied to both of synthetic data sets and RNAi high content screen (HCS) images with ground truth labels.

KW - Gap statistics

KW - High content screen

KW - Phenotype discovery

KW - RNA interference

UR - http://www.scopus.com/inward/record.url?scp=71449123412&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=71449123412&partnerID=8YFLogxK

U2 - 10.1063/1.2816647

DO - 10.1063/1.2816647

M3 - Conference contribution

AN - SCOPUS:71449123412

SN - 9780735404663

VL - 952

SP - 86

EP - 95

BT - Computational Models For Life Sciences (CMLS '07) - 2007 International Symposium

T2 - 2007 International Symposium on Computational Models for Life Sciences, CMLS '07

Y2 - 17 December 2007 through 19 December 2007

ER -

Online phenotype discovery in high-content RNAi screens using gap statistics

Abstract

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this