Publications by authors named "Thomas Simos"
Assessment of optimized Markov models in protein fold classification.
J Bioinform Comput Biol
August 2014
Article Synopsis
- Protein fold classification is important for understanding protein structure, and this study tested optimization strategies on different models to improve accuracy.
- A Hidden Markov Model (HMM) with a simplified state-space was evaluated against proteins with unknown structures using optimization scores.
- The optimized HMM outperformed traditional methods, achieving a fold classification accuracy of 41.4%, compared to 38% for Sequence Alignment and Modeling (SAM).
Hepatitis B virus (HBV) and hepatitis C virus (HCV) infection are the major causes of chronic liver disease, cirrhosis and hepatocellular carcinoma (HCC). The resolution or chronicity of acute infection is dependent on a complex interplay between virus and innate/adaptive immunity. The mechanisms that lead a significant proportion of patients to more severe liver disease are not clearly defined and involve virus induced host gene/protein alterations.
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