H
Hanchuan Peng
Researcher at Southeast University
Publications - 179
Citations - 30111
Hanchuan Peng is an academic researcher from Southeast University. The author has contributed to research in topics: Tracing & Image segmentation. The author has an hindex of 44, co-authored 164 publications receiving 25598 citations. Previous affiliations of Hanchuan Peng include Howard Hughes Medical Institute & Janelia Farm Research Campus.
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Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
TL;DR: In this article, the maximal statistical dependency criterion based on mutual information (mRMR) was proposed to select good features according to the maximal dependency condition. But the problem of feature selection is not solved by directly implementing mRMR.
Feature selection based on mutual information: criteria ofmax-dependency, max-relevance, and min-redundancy
TL;DR: This work derives an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection, and presents a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers).
Journal ArticleDOI
A mesoscale connectome of the mouse brain
Seung Wook Oh,Julie A. Harris,Lydia Ng,Brent Winslow,Nicholas Cain,Stefan Mihalas,Quanxin Wang,Chris Lau,Leonard Kuan,Alex M. Henry,Marty Mortrud,Benjamin Ouellette,Thuc Nghi Nguyen,Staci A. Sorensen,Clifford R. Slaughterbeck,Wayne Wakeman,Yang Li,David Feng,Anh Ho,Eric Nicholas,Karla E. Hirokawa,Phillip Bohn,Kevin M. Joines,Hanchuan Peng,Michael Hawrylycz,John W. Phillips,John G. Hohmann,Paul Wohnoutka,Charles R. Gerfen,Christof Koch,Amy Bernard,Chinh Dang,Allan R. Jones,Hongkui Zeng +33 more
TL;DR: A brain-wide, cellular-level, mesoscale connectome for the mouse, using enhanced green fluorescent protein-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain.
Journal ArticleDOI
Minimum redundancy feature selection from microarray gene expression data.
Chris Ding,Hanchuan Peng +1 more
TL;DR: How to selecting a small subset out of the thousands of genes in microarray data is important for accurate classification of phenotypes.
Journal ArticleDOI
A GAL4-Driver Line Resource for Drosophila Neurobiology
Arnim Jenett,Gerald M. Rubin,Teri-T B. Ngo,David Shepherd,Christine Murphy,Heather Dionne,Barret D. Pfeiffer,Amanda Cavallaro,Donald Hall,Jennifer Jeter,Nirmala Iyer,Dona Fetter,Joanna H. Hausenfluck,Hanchuan Peng,Eric T. Trautman,Robert Svirskas,Eugene W. Myers,Zbigniew R. Iwinski,Yoshinori Aso,Gina M. DePasquale,Adrianne Enos,Phuson Hulamm,S. Lam,Hsing-Hsi Li,Todd R. Laverty,Fuhui Long,Lei Qu,Sean D. Murphy,Konrad Rokicki,Todd Safford,Kshiti Shaw,Julie H. Simpson,Allison Sowell,Susana Tae,Yang Yu,Christopher T. Zugates +35 more
TL;DR: The utility of 7,000 transgenic lines of Drosophila melanogaster for identifying novel neuronal cell types, revealing brain asymmetry, and describing the nature and extent of neuronal shape stereotypy is illustrated.