Protein Sequence Similarity Analysis Using Computational Techniques

Nikhila, K.S.; Nair, Vrinda V.

doi:10.1016/j.matpr.2017.11.139

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…As pointed out in recent reports, , we will carry out studies to evaluate these novel biomacromolecular descriptors in several representative protein science applications ( e.g. enzyme discrimination, protein similarity evaluation, , and so on), to determine in which of them these novel descriptors have better performance than previous approaches.…”

Section: Future Outlookmentioning

confidence: 99%

MuLiMs-MCoMPAs: A Novel Multiplatform Framework to Compute Tensor Algebra-Based Three-Dimensional Protein Descriptors

Contreras-Torres

Marrero-Ponce

Terán

et al. 2019

J. Chem. Inf. Model.

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This report introduces the MuLiMs-MCoMPAs software (acronym for Multi-Linear Maps based on N-Metric and Contact Matrices of 3D Protein and Amino-acid weightings), designed to compute tensor-based 3D protein structural descriptors by applying two- and three-linear algebraic forms. Moreover, these descriptors contemplate generalizing components such as novel 3D protein structural representations, (dis)similarity metrics, and multimetrics to extract geometrical related information between two and three amino acids, weighting schemes based on amino acid properties, matrix normalization procedures that consider simple-stochastic and mutual probability transformations, topological and geometrical cutoffs, amino acid, and group-based MD calculations, and aggregation operators for merging amino acidic and group MDs. The MuLiMs-MCoMPAs software, which belongs to the ToMoCoMD-CAMPS suite, was developed in Java (version 1.8) using the Chemistry Development Kit (CDK) (version 1.4.19) and the Jmol libraries. This software implemented a divide-and-conquer strategy to parallelize the computation of the indices as well as modules for data preprocessing and batch computing functionalities. Furthermore, it consists of two components: (i) a desktop-graphical user interface (GUI) and (ii) an API library. The relevance of this novel approach is demonstrated through two analyses that considered Shannon’s entropy-based variability and a principal component analysis. These studies showed that the MuLiMs-MCoMPAs’ three-linear descriptor family contains higher informational entropy than several other descriptors generated with available computation tools. Moreover, the MuLiMs-MCoMPAs indices capture additional orthogonal information to the one codified by the available calculation approaches. As a result, two sets of suggested theoretical configurations that contain 13648 two-linear indices and 20263 three-linear indices are available for download at . Furthermore, as a demonstration of the applicability and easy integration of the MuLiMs library into a QSAR-based expert system, a software application (ProStAF) was generated to predict SCOP protein structural classes and folding rate. It can thus be anticipated that the MuLiMs-MCoMPAs framework will turn into a valuable contribution to the chem- and bioinformatics research fields.

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Section: Future Outlookmentioning

confidence: 99%

MuLiMs-MCoMPAs: A Novel Multiplatform Framework to Compute Tensor Algebra-Based Three-Dimensional Protein Descriptors

Contreras-Torres

Marrero-Ponce

Terán

et al. 2019

J. Chem. Inf. Model.

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“…Thus, it is possible to reduce the number of experiments but still survey much input information independently. This method has recently applied in different fields of studies [16][17][18]20]. The dimensional analysis was used in electrostatic precipitators (ESP) model building, showing both the reduction in effort and more effective modeling that can result.…”

Section: Introductionmentioning

confidence: 99%

Application of Similarity Method and Dimensional Analysis in Determining the Performance Parameters of Agitator Paddles for Caltex Aquatex 3180 Cutting Oil

Tam

Quan²

2020

Int. J. Eng. Tech. Mgmt. Res.

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Aquatex 3180 is the general purpose soluble oil, formulated for use in a wide variety of machining operations. In fact, the natural diffusion in the liquid is very slow, especially the mixing ratio, and the homogeneity of the solution is difficult to achieve according to the manufacturer's recommendation. Hence, the agitator is required to improve the uniformity of the solution in that the obtained cutting fluid can be effectively used in machining processes to fulfill the role of cooling and lubricating. In this work, the application of the similarity method and dimensional analysis for studying agitator model for mixing Aquatex 3180 cutting oil to build the set of input parameters in the experimental process. The results reveal that the input parameters in the study of the agitator model using 9 similarity criterions πi (i = 1 ... 9) instead of 12 independent parameters. In addition, the standard π2 can characterize the displacement properties of the fluid flow considering the influence of gravity. It means that the number of experiments reduce but still ensure that many experimental input parameters are still guaranteed, therefore ensuring proper description of the actual operation of the machine.

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Prediction and Analysis of Pseudomonas Aeruginosa Promoters Based on Sequence Features

Liu

Guo

et al. 2019

2019 IEEE 11th International Conference on Advanced Infocomm Technology (ICAIT)

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Protein Sequence Similarity Analysis Using Computational Techniques

Cited by 5 publications

References 13 publications

MuLiMs-MCoMPAs: A Novel Multiplatform Framework to Compute Tensor Algebra-Based Three-Dimensional Protein Descriptors

MuLiMs-MCoMPAs: A Novel Multiplatform Framework to Compute Tensor Algebra-Based Three-Dimensional Protein Descriptors

Application of Similarity Method and Dimensional Analysis in Determining the Performance Parameters of Agitator Paddles for Caltex Aquatex 3180 Cutting Oil

Prediction and Analysis of Pseudomonas Aeruginosa Promoters Based on Sequence Features

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