Background: It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases...
Pengyi Yang, Joshua W. K. Ho, Albert Y. Zomaya, Bi...
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Background: Profile hidden Markov models (profile-HMMs) are sensitive tools for remote protein homology detection, but the main scoring algorithms, Viterbi or Forward, require con...
Background: Transcription Factors (TFs) and microRNAs (miRNAs) are key players for gene expression regulation in higher eukaryotes. In the last years, a large amount of bioinforma...
Olivier Friard, Angela Re, Daniela Taverna, Michel...
Background: Quantitative models for transcriptional regulation have shown great promise for advancing our understanding of the biological mechanisms underlying gene regulation. Ho...
Denis C. Bauer, Fabian A. Buske, Timothy L. Bailey
Background: The pan-genome of a bacterial species consists of a core and an accessory gene pool. The accessory genome is thought to be an important source of genetic variability i...
Chad Laing, Cody Buchanan, Eduardo N. Taboada, Yon...
Background: Genome-wide association studies have been successful in finding common variants influencing common traits. However, these associations only account for a fraction of t...
Robert Lawrence, Aaron G. Day-Williams, Katherine ...
Background: Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-ba...
Frederick A. Matsen III, Robin B. Kodner, E. Virgi...
Background: The goal of class prediction studies is to develop rules to accurately predict the class membership of new samples. The rules are derived using the values of the varia...
Background: To further understand the implementation of hyperparameters re-estimation technique in Bayesian hierarchical model, we added two more prior assumptions over the weight...