output
20032026
most citedA Pseudo DNA Cryptography Method

304 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2019Show all

6 papers · 1 filter

cs.CL2019★ 30 cited

Knowledge-guided Convolutional Networks for Chemical-Disease Relation Extraction

Huiwei Zhou, Chengkun Lang, Zhuang Liu +3

Background: Automatic extraction of chemical-disease relations (CDR) from unstructured text is of essential importance for disease treatment and drug development. Meanwhile, biomed…

cs.CL2019★ 7 cited

Improving Neural Protein-Protein Interaction Extraction with Knowledge Selection

Huiwei Zhou, Xuefei Li, Weihong Yao +4

Protein-protein interaction (PPI) extraction from published scientific literature provides additional support for precision medicine efforts. Meanwhile, knowledge bases (KBs) conta…

math.OC2019

Finite-Horizon Optimal Control of Boolean Control Networks: A Unified Graph-Theoretical Approach

Shuhua Gao, Changkai Sun, Cheng Xiang +2

This paper investigates the finite-horizon optimal control (FHOC) problem of Boolean control networks (BCNs) from a graph theory perspective. We first formulate two general problem…

cs.DL2019★ 26 cited

Nine Million Book Items and Eleven Million Citations: A Study of Book-Based Scholarly Communication Using OpenCitations

Yongjun Zhu, Erjia Yan, Silvio Peroni +1

Books have been widely used to share information and contribute to human knowledge. However, the quantitative use of books as a method of scholarly communication is relatively unex…

astro-ph.IM2019★ 37 cited

The Detailed Science Case for the Maunakea Spectroscopic Explorer, 2019 edition

The MSE Science Team, Carine Babusiaux, Maria Bergemann +258

(Abridged) The Maunakea Spectroscopic Explorer (MSE) is an end-to-end science platform for the design, execution and scientific exploitation of spectroscopic surveys. It will unvei…

cs.CV2019

Top-view Trajectories: A Pedestrian Dataset of Vehicle-Crowd Interaction from Controlled Experiments and Crowded Campus

Dongfang Yang, Linhui Li, Keith Redmill +1

Predicting the collective motion of a group of pedestrians (a crowd) under the vehicle influence is essential for the development of autonomous vehicles to deal with mixed urban sc…