Protein functional module identification method combining topological features and gene expression data (open access)

Protein functional module identification method combining topological features and gene expression data

Article conducting an intensive study on the problems of low recognition efficiency and noise in the overlapping structure of protein functional modules, based on topological characteristics of PPI network. Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification. The experimental results show that the ECTG algorithm can detect protein functional modules better.
Date: June 8, 2021
Creator: Zhao, Zihao; Xu, Wenjun; Chen, Aiwen; Han, Yueyue; Xia, Shengrong; Xiang, ChuLei et al.
System: The UNT Digital Library
Weak-Light Image Enhancement Method Based on Adaptive Local Gamma Transform and Color Compensation (open access)

Weak-Light Image Enhancement Method Based on Adaptive Local Gamma Transform and Color Compensation

This article proposes a correction method for image enhancement models based on an adaptive local gamma transformation and color compensation inspired by the illumination reflection model. It is demonstrated that the proposed method adaptively reduces the influence of uneven illumination to avoid overenhancement and improves the visual effect of low-light images.
Date: June 25, 2021
Creator: Wang, Wencheng; Yuan, Xiaohui; Chen, Zhenxue; Wu, Xiaojin & Gao, Zairui
System: The UNT Digital Library
Design and Assessment of a Task-Driven Introductory Data Science Course Taught Concurrently in Multiple Languages: Python, R, and MATLAB (open access)

Design and Assessment of a Task-Driven Introductory Data Science Course Taught Concurrently in Multiple Languages: Python, R, and MATLAB

This article is from the 26th ACM Conference on Innovation and Technology in Computer Science Education and discusses the design, effectiveness, and curricular impacts of an introductory data science course focused on practical programming skills and allowing students to concurrently complete the course in Python, R, or MATLAB. Students indicated a preference for the multi-language course design and the course became the recommended first programming course for a newly developed and approved undergraduate data science majors.
Date: June 26, 2021
Creator: Xiao, Ting; Greenberg, Ronald I. & Albert, Mark
System: The UNT Digital Library