Secondary Structure Prediction Based on Statistical Mechanics
نویسندگان
چکیده
Recent genome science has been developing from two sides: one is biological evolution due to mutation of DNA sequence and the other is biological function of protein molecules formed according to amino acid sequences. We have devoted ourselves to elucidate the mechanism of protein folding, and to develop the method for protein structure prediction [1, 2]. Our method has successfully yielded the native-like tertiary structures of various proteins, by using secondary structure information. Secondary structure prediction with a high precision, however, is essential to proteins of unknown structures. Our method for three-state (α-helix, β-strand and coil) prediction have reached the prediction accuracy of only 68%, which accuracy may not be sufficient for packing secondary structures into correct tertiary structure. Some methods [3] for secondary structure prediction exceed a little the accuracy achieved by our method. Contrary to the other methods, we can analyze the reasons for the poor accuracy and thus are attempting to improve the present accuracy. In this article, we describe the way to improve the prediction accuracy presented in Genome Informatics Workshop IV (GIW ’93) [4].
منابع مشابه
Protein Secondary Structure Prediction: a Literature Review with Focus on Machine Learning Approaches
DNA sequence, containing all genetic traits is not a functional entity. Instead, it transfers to protein sequences by transcription and translation processes. This protein sequence takes on a 3D structure later, which is a functional unit and can manage biological interactions using the information encoded in DNA. Every life process one can figure is undertaken by proteins with specific functio...
متن کاملFracture mechanics-based life prediction of a riveted lap joint
In this paper, three-dimensional modeling of the fatigue crack growth profiles was performed in a simple riveted lap joint. Simulation results showed that mode I was dominated on the one side of the plates and the crack straightly grew on this side, while the other side of the plates was in a mixed-mode condition and the crack propagation path was not straight on this side. Afterward, the fract...
متن کاملCONTRAfold: RNA secondary structure prediction without physics-based models
MOTIVATION For several decades, free energy minimization methods have been the dominant strategy for single sequence RNA secondary structure prediction. More recently, stochastic context-free grammars (SCFGs) have emerged as an alternative probabilistic methodology for modeling RNA structure. Unlike physics-based methods, which rely on thousands of experimentally-measured thermodynamic paramete...
متن کاملDevelopment of Lifetime Prediction Model of Lithium-Ion Battery Based on Minimizing Prediction Errors of Cycling and Operational Time Degradation Using Genetic Algorithm
Accurate lifetime prediction of lithium-ion batteries is a great challenge for the researchers and engineers involved in battery applications in electric vehicles and satellites. In this study, a semi-empirical model is introduced to predict the capacity loss of lithium-ion batteries as a function of charge and discharge cycles, operational time, and temperature. The model parameters are obtai...
متن کاملPrediction Based on Type-II Censored Coherent System Lifetime Data under a Proportional Reversed Hazard Rate Model
In this paper, we discuss the prediction problem based on censored coherent system lifetime data when the system structure is known and the component lifetime follows the proportional reversed hazard model. Different point and interval predictors based on classical and Bayesian approaches are derived. A numerical example is presented to illustrate the prediction methods used in this paper. Mont...
متن کامل