Institution
National Cheng Kung University
Education•Tainan City, Taiwan•
About: National Cheng Kung University is a education organization based out in Tainan City, Taiwan. It is known for research contribution in the topics: Population & Thin film. The organization has 49723 authors who have published 69799 publications receiving 1437420 citations. The organization is also known as: NCKU.
Topics: Population, Thin film, Microstructure, Dielectric, Heat transfer
Papers published on a yearly basis
Papers
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TL;DR: The PlantPAN 3.0 can not only be efficiently used to investigate critical cis- and trans-regulatory elements in plant promoters, but also to reconstruct high-confidence relationships among TF–targets under specific conditions.
Abstract: The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN.itps.ncku.edu.tw/) is an effective resource for predicting regulatory elements and reconstructing transcriptional regulatory networks for plant genes. In this release (PlantPAN 3.0), 17 230 TFs were collected from 78 plant species. To explore regulatory landscapes, genomic locations of TFBSs have been captured from 662 public ChIP-seq samples using standard data processing. A total of 1 233 999 regulatory linkages were identified from 99 regulatory factors (TFs, histones and other DNA-binding proteins) and their target genes across seven species. Additionally, this new version added 2449 matrices extracted from ChIP-seq peaks for cis-regulatory element prediction. In addition to integrated ChIP-seq data, four major improvements were provided for more comprehensive information of TF binding events, including (i) 1107 experimentally verified TF matrices from the literature, (ii) gene regulation network comparison between two species, (iii) 3D structures of TFs and TF-DNA complexes and (iv) condition-specific co-expression networks of TFs and their target genes extended to four species. The PlantPAN 3.0 can not only be efficiently used to investigate critical cis- and trans-regulatory elements in plant promoters, but also to reconstruct high-confidence relationships among TF-targets under specific conditions.
263 citations
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TL;DR: This material is based upon work supported by the National Science Foundation, Riksbankens Jubileumsfond, the Swedish Research Council, and the University of Gothenburg as well as internal grants from the Vice-Chancellor's office, the Dean of the College of Social Sciences and the Department of Political Science at University of Gethenburg.
Abstract: This material is based upon work supported by the National Science Foundation (SES-1423944, PI: Daniel Pemstein), Riksbankens Jubileumsfond (Grant M13-0559:1, PI: Staffan I. Lindberg), the Swedish Research Council (2013.0166, PI: Staffan I. Lindberg and Jan Teorell), the Knut and Alice Wallenberg Foundation (PI: Staffan I. Lindberg), and the University of Gothenburg (E 2013/43); as well as internal grants from the Vice-Chancellor’s office, the Dean of the College of Social Sciences, and the Department of Political Science at University of Gothenburg. Marquardt acknowledges research support from the Russian Academic Excellence Project ‘5-100.’ We performed simulations and other computational tasks using resources provided by the Notre Dame Center for Research Computing (CRC) through the High Performance Computing section and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre in Sweden (SNIC 2016/1-382, SNIC 2017/1-406 and 2017/1-68). We specifically acknowledge the assistance of In-Saeng Suh at CRC and Johan Raber and Peter Mu nger at SNIC in facilitating our use of their respective systems.
262 citations
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TL;DR: Methods for arsenic removal suitable to be applied in Latin American waters are summarized and commented, and emphasis is made in emergent decentralized economical methods as the use of inexpensive natural adsorbents, solar light technologies or biological treatments, as essential to palliate the situation in poor, isolated and dispersed populations of Latin American regions.
262 citations
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TL;DR: Without significant difference in the prevalence of expressing hypermucoviscosity phenotype and carriage of rmpA and aerobactin genes, these virulent non-K1/K2 isolates are as capable of causing primary liver abscesses in Klebsiella pneumoniae patients treated at 2 medical centers in Taiwan.
262 citations
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TL;DR: The result demonstrates that the proposed recurrent neural classifier using the energy features extracted from characteristic waves of EEG signals can classify sleep stages more efficiently and accurately using only a single EEG channel.
262 citations
Authors
Showing all 49872 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
Yang Yang | 164 | 2704 | 144071 |
R. E. Hughes | 154 | 1312 | 110970 |
Mercouri G. Kanatzidis | 152 | 1854 | 113022 |
Thomas J. Smith | 140 | 1775 | 113919 |
Hui Li | 135 | 2982 | 105903 |
Gerald M. Reaven | 133 | 799 | 80351 |
Chi-Huey Wong | 129 | 1220 | 66349 |
Joseph P. Vacanti | 119 | 441 | 50739 |
Kai Nan An | 109 | 953 | 51638 |
Ding-Shinn Chen | 104 | 774 | 46068 |
James D. Neaton | 101 | 331 | 64719 |
David C. Christiani | 100 | 1052 | 55399 |
Jo Shu Chang | 99 | 639 | 37487 |
Yu Shyr | 98 | 542 | 39527 |