[PDF] Top 20 Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction
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Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction
... only sequence information, using an optimized SVM with RBF ...the structure-like behavior of IDPs in disease-associated ...of protein residues, a useful structural property that defines protein’s ... See full document
229
The development of machine learning based software for predicting protein-protein interactions and protein function from protein primary structure
... that protein-protein interactions are sometimes confused with metabolic ...and protein interaction maps are similar, there are a number of significant differences: While metabolic pathways ... See full document
159
Comparative Study of Machine Learning Models in Protein Structure Prediction
... Real Coded Genetic Algorithms (RCGA) is one of the most popular optimization method among the evolutionary algorithm (EAS) .it’s a population based stochastic search approach and in general can be regarded as a ... See full document
7
Prediction of DNA-binding proteins from relational features
... vector machine classifier using the pro- tein’s overall charge and its overall and surface amino acid ...classifier based on the amino acid composi- tion, the asymmetry of the spatial distribution of specific ... See full document
11
P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure
... site prediction from protein structure has many applications related to elucidation of protein function and structure based drug ...template based or available only as web ... See full document
12
Protein disorderness based prediction of essential genes of Saccharomyces cerevisiae: A machine learning approach
... and machine learning methods have been attempted to predict the essential genes of the organisms mentioned above (Plaimas et al, Chen et al, Heber et ...the protein-protein interaction ... See full document
5
Identification of protein functions using a machine-learning approach based on sequence-derived properties
... Figure 4 presents the results of analysis of the raw dataset for four features, when the proteins were classified using the random forest method. The mean values of the four selected features for gluconate utilisation ... See full document
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Protein Function Prediction from Protein Interaction Network Using Clustering and Sequence of Amino Acid
... network-flow based algorithm that exploits the underlying structure of protein interaction maps in order to predict protein ...molecular interaction networks has made possible ... See full document
5
Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate
... of protein function is essential for the study of biological processes, the understanding of disease mechanism and the exploration of novel therapeutic ...for protein function ...functions based on ... See full document
22
Prediction of protein-protein interaction types using machine learning approaches
... non-obligate protein-protein ...the prediction. The prediction approach relies on two state-of-the-art classification techniques of linear dimensionality reduction (LDR) [24] and support ... See full document
215
Algorithmic approaches to protein-protein interaction site prediction
... uses machine learning on fea- ture vectors derived from sequence ...each protein, a peptide is extracted with the residue in question serving as its center, accounting for the local environ- ... See full document
21
Enhanced Self Organizing Map Neural Network for DNA Sequence Classification
... bioinformatics: protein structure prediction (using both sequence matching and machine learning techniques); and data ... See full document
9
Homology modeling a fast tool for drug discovery: Current perspectives
... of protein-ligand complexes; in which the protein molecules act energetically in the course of ...of protein-ligand interaction will be very important for structure based drug ... See full document
17
Machine Learning based Approach for protein Function Prediction using Sequence Derived Properties
... In this paper 857 sequence-derived features such as amino acid composition, dipeptide composition, correlation, composition, transition and distribution and pseudo amino acid composition[r] ... See full document
5
Interdomain interactions of the transactive response DNA binding protein 43 kDa (TDP-43)
... domain interaction by RNA-binding or post-translational modification, for example, the NES would be exposed and export of TDP-43 could ...The structure formed by the N-terminal domain is just starting to be ... See full document
136
Domain-Based Predictive Models for Protein-Protein Interaction Prediction
... This structure can capture various combinations between domains, instead of only two domains at a ...a protein pair to be interact- ing if the output node value is larger than or equal to certain ... See full document
8
Sequence to Sequence Learning for Event Prediction
... Evaluation based on paraphrase sets BLEU scores are difficult to interpret for the task: BLEU is a surface-based measure as mentioned in (Qin and Specia, 2015), while event prediction is essentially ... See full document
6
Index Terms- Big data analytics, Machine Learning, Healthcare, Disease Detection, Medical Data Analysis.
... the machine learning based disease prediction from medical field and uses the big data concept, which means the machine learning is a data mining techniques but this technique ... See full document
7
Tutorial: De mystifying Neural MT
... Neural Statistical Machine Translation Neural Machine Translation Encoder Decoder Sequence-to-sequence learning: Encoder Sequence-to-sequence learning: Decoder Let’s use a simple NN for [r] ... See full document
84
Prediction of protein Post-Translational Modification sites: An overview
... The PTMs of proteins have been detected by a variety of experimental techniques including the mass spectrometry (MS) [5,6], liquid chromatography [7], radioactive chemical method [8], chromatin immune precipitation ... See full document
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