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Full-Text Articles in Computer Sciences

Robust Inference Of Kinase Activity Using Functional Networks, Serhan Yılmaz, Marzieh Ayati, Daniela Schlatzer, A. Ercüment Çiçek, Mark A. Chance, Mehmet Koyutürk Feb 2021

Robust Inference Of Kinase Activity Using Functional Networks, Serhan Yılmaz, Marzieh Ayati, Daniela Schlatzer, A. Ercüment Çiçek, Mark A. Chance, Mehmet Koyutürk

Computer Science Faculty Publications and Presentations

Mass spectrometry enables high-throughput screening of phosphoproteins across a broad range of biological contexts. When complemented by computational algorithms, phospho-proteomic data allows the inference of kinase activity, facilitating the identification of dysregulated kinases in various diseases including cancer, Alzheimer’s disease and Parkinson’s disease. To enhance the reliability of kinase activity inference, we present a network-based framework, RoKAI, that integrates various sources of functional information to capture coordinated changes in signaling. Through computational experiments, we show that phosphorylation of sites in the functional neighborhood of a kinase are significantly predictive of its activity. The incorporation of this knowledge in RoKAI consistently …


Developing Big Data Projects In Open University Engineering Courses: Lessons Learned, Juan A. Lara, Aurea Anguera De Sojo, Shadi Aljawarneh, Robert P. Schumaker, Bassam Al-Shargabi Feb 2020

Developing Big Data Projects In Open University Engineering Courses: Lessons Learned, Juan A. Lara, Aurea Anguera De Sojo, Shadi Aljawarneh, Robert P. Schumaker, Bassam Al-Shargabi

Computer Science Faculty Publications and Presentations

Big Data courses in which students are asked to carry out Big Data projects are becoming more frequent as a part of University Engineering curriculum. In these courses, instructors and students must face a series of special characteristics, difficulties and challenges that it is important to know about beforehand, so the lecturer can better plan the subject and manage the teaching methods in order to prevent students' academic dropout and low performance. The goal of this research is to approach this problem by sharing the lessons learned in the process of teaching e-learning courses where students are required to develop …


Analyzing The Relationship Between Human Behavior And Indoor Air Quality, Beiyu Lin, Yibo Huangfu, Nathan Lima, Bertram Jobson, Max Kirk, Patrick O’Keeffe, Shelley N. Pressley, Von Walden, Brian Lamb, Diane J. Cook Aug 2017

Analyzing The Relationship Between Human Behavior And Indoor Air Quality, Beiyu Lin, Yibo Huangfu, Nathan Lima, Bertram Jobson, Max Kirk, Patrick O’Keeffe, Shelley N. Pressley, Von Walden, Brian Lamb, Diane J. Cook

Computer Science Faculty Publications and Presentations

In the coming decades, as we experience global population growth and global aging issues, there will be corresponding concerns about the quality of the air we experience inside and outside buildings. Because we can anticipate that there will be behavioral changes that accompany population growth and aging, we examine the relationship between home occupant behavior and indoor air quality. To do this, we collect both sensor-based behavior data and chemical indoor air quality measurements in smart home environments. We introduce a novel machine learning-based approach to quantify the correlation between smart home features and chemical measurements of air quality, and …


A Theory Of Name Resolution, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth Jan 2015

A Theory Of Name Resolution, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth

Computer Science Faculty Publications and Presentations

We describe a language-independent theory for name binding and resolution, suitable for programming languages with complex scoping rules including both lexical scoping and modules. We formulate name resolution as a two-stage problem. First a language-independent scope graph is constructed using language-specific rules from an abstract syntax tree. Then references in the scope graph are resolved to corresponding declarations using a language-independent resolution process. We introduce a resolution calculus as a concise, declarative, and language- independent specification of name resolution. We develop a resolution algorithm that is sound and complete with respect to the calculus. Based on the resolution calculus we …


Guiding Data-Driven Transportation Decisions, Kristin A. Tufte, Basem Elazzabi, Nathan Hall, Morgan Harvey, Kath Knobe, David Maier, Veronika Margaret Megler Jan 2014

Guiding Data-Driven Transportation Decisions, Kristin A. Tufte, Basem Elazzabi, Nathan Hall, Morgan Harvey, Kath Knobe, David Maier, Veronika Margaret Megler

Computer Science Faculty Publications and Presentations

Urban transportation professionals are under increasing pressure to perform data-driven decision making and to provide data-driven performance metrics. This pressure comes from sources including the federal government and is driven, in part, by the increased volume and variety of transportation data available. This sudden increase of data is partially a result of improved technology for sensors and mobile devices as well as reduced device and storage costs. However, using this proliferation of data for decisions and performance metrics is proving to be difficult. In this paper, we describe a proposed structure for a system to support data-driven decision making. A …


Data Near Here: Bringing Relevant Data Closer To Scientists, Veronika M. Megler, David Maier May 2013

Data Near Here: Bringing Relevant Data Closer To Scientists, Veronika M. Megler, David Maier

Computer Science Faculty Publications and Presentations

Large scientific repositories run the risk of losing value as their holdings expand, if it means increased effort for a scientist to locate particular datasets of interest. We discuss the challenges that scientists face in locating relevant data, and present our work in applying Information Retrieval techniques to dataset search, as embodied in the Data Near Here application.