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Full-Text Articles in Physical Sciences and Mathematics
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Associate Professor Yan-Xia Lin
No abstract provided.
The Probability Distribution Of Distance Tss-Tls Is Organism Characteristic And Can Be Used For Promoter Prediction, Yun Dai, Ren Zhang, Yan-Xia Lin
The Probability Distribution Of Distance Tss-Tls Is Organism Characteristic And Can Be Used For Promoter Prediction, Yun Dai, Ren Zhang, Yan-Xia Lin
Associate Professor Yan-Xia Lin
Transcription is a complicated process which involves the interactions of promoter cis-elements with multiple trans-protein factors. The specific interactions rely not only on the specific sequence recognition between the cis- and trans-factors but also on certain spatial arrangement of the factors in a complex. The relative positioning of involved cis-elements provides the framework for such a spatial arrangement. The distance distribution between gene transcription and translation start sites (TSS-TLS) is the subject of the present study to test an assumption that over evolution, the TSS-TLS distance becomes a distinct character for a given organism. Four representative organisms (Escherichia cloi, Saccharomyces …
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Alexandra Burden, Lecturer, School of Mathematics and Applied Statistics, Faculty of Informatics
No abstract provided.
Exploring The Impact Of Knowledge And Social Environment On Influenza Prevention And Transmission In Midwestern United States High School Students, William L. Romine, Tanvi Banerjee, William S. Barrow, William R. Folk
Exploring The Impact Of Knowledge And Social Environment On Influenza Prevention And Transmission In Midwestern United States High School Students, William L. Romine, Tanvi Banerjee, William S. Barrow, William R. Folk
Kno.e.sis Publications
We used data from a convenience sample of 410 Midwestern United States students from six secondary schools to develop parsimonious models for explaining and predicting precautions and illness related to influenza. Scores for knowledge and perceptions were obtained using two-parameter Item Response Theory (IRT) models. Relationships between outcome variables and predictors were verified using Pearson and Spearman correlations, and nested [student within school] fixed effects multinomial logistic regression models were specified from these using Akaike’s Information Criterion (AIC). Neural network models were then formulated as classifiers using 10-fold cross validation to predict precautions and illness. Perceived barriers against taking precautions …
Demographic Prediction Of Mobile User From Phone Usage, Shahram Mohrehkesh, Shuiwang Ji, Tamer Nadeem, Michele C. Weigle
Demographic Prediction Of Mobile User From Phone Usage, Shahram Mohrehkesh, Shuiwang Ji, Tamer Nadeem, Michele C. Weigle
Computer Science Faculty Publications
In this paper, we describe how we use the mobile phone usage of users to predict their demographic attributes. Using call log, visited GSM cells information, visited Bluetooth devices, visited Wireless LAN devices, accelerometer data, and so on, we predict the gender, age, marital status, job and number of people in household of users. The accuracy of developed classifiers for these classification problems ranges from 45-87% depending upon the particular classification problem.