Classification of Amino Acid Using Micro-electrical Model

2020 ◽  
pp. 125-132
Author(s):  
Tanusree Roy ◽  
Pranabesh Bhattacharjee
Keyword(s):  
Amino Acid ◽  
Electrical Model

scholarly journals A classification of nucleotide-diphospho-sugar glycosyltransferases based on amino acid sequence similarities

1998 ◽  
Vol 329 (3) ◽  
pp. 719-719 ◽  
Author(s):  
J. A. CAMPBELL ◽  
G. J. DAVIES ◽  
V. BULONE ◽  
B. HENRISSAT
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Sequence Similarities

Analysis of HCV’s Linearity Using Support Vector Machine (SVM)

2014 ◽  
Vol 548-549 ◽  
pp. 1265-1269
Author(s):  
Yun Sik Hwang ◽  
Byeong Joo Jun ◽  
Tae Seon Yoon
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Hepatitis C Virus ◽  
Data Analysis ◽  
Hepatitis C ◽  
Amino Acid ◽  
Support Vector ◽  
Svm Algorithm ◽  
Genetic Patterns

As the stage of bioinformatics has been upgraded, classification of certain pathogen has been improved into a new manner. The main topic of this research is genetic singularity of HCV (Hepatitis C Virus) and our objective is to assay features of the HCV's amino acid under usage of Support Vector Machine (SVM) algorithm. HCV data used in our experiment has 10 kinds of sequences and 257 kinds of data. According to data analysis, some peculiar genetic patterns of HCV’s linearity that discord pre-existing neural network and C5.0 were found.

scholarly journals A novel method for achieving an optimal classification of the proteinogenic amino acids

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Andre Then ◽  
Karel Mácha ◽  
Bashar Ibrahim ◽  
Stefan Schuster
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Interaction Potential ◽  
Binary Separation ◽  
Multiple Alignments ◽  
Novel Method ◽  
Optimal Classification ◽  
Helix Propensity ◽  
Α Helix

Abstract The classification of proteinogenic amino acids is crucial for understanding their commonalities as well as their differences to provide a hint for why life settled on the usage of precisely those amino acids. It is also crucial for predicting electrostatic, hydrophobic, stacking and other interactions, for assessing conservation in multiple alignments and many other applications. While several methods have been proposed to find “the” optimal classification, they have several shortcomings, such as the lack of efficiency and interpretability or an unnecessarily high number of discriminating features. In this study, we propose a novel method involving a repeated binary separation via a minimum amount of five features (such as hydrophobicity or volume) expressed by numerical values for amino acid characteristics. The features are extracted from the AAindex database. By simple separation at the medians, we successfully derive the five properties volume, electron–ion-interaction potential, hydrophobicity, α-helix propensity, and π-helix propensity. We extend our analysis to separations other than by the median. We further score our combinations based on how natural the separations are.

Two-dimensional classification of amphiphilic monomers based on interfacial and partitioning properties. 2. Amino acids and amino acid residues

2006 ◽  
Vol 284 (6) ◽  
pp. 575-585 ◽  
Author(s):  
Ivan M. Okhapkin ◽  
Andrei A. Askadskii ◽  
Vladimir A. Markov ◽  
Elena E. Makhaeva ◽  
Alexei R. Khokhlov
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Two Dimensional ◽  
Amino Acid Residues ◽  
Dimensional Classification

scholarly journals Genomic Characterization of Severe Acute Respiratory Syndrome-Related Coronavirus in European Bats and Classification of Coronaviruses Based on Partial RNA-Dependent RNA Polymerase Gene Sequences

2010 ◽  
Vol 84 (21) ◽  
pp. 11336-11349 ◽  
Author(s):  
Jan Felix Drexler ◽  
Florian Gloza-Rausch ◽  
Jörg Glende ◽  
Victor Max Corman ◽  
Doreen Muth ◽  
...  
Keyword(s):  
Amino Acid ◽  
Severe Acute Respiratory Syndrome ◽  
Surface Expression ◽  
Emerging Viruses ◽  
Reading Frame ◽  
High Frequencies ◽  
Nyctalus Leisleri ◽  
Genomic Characterization

ABSTRACT Bats may host emerging viruses, including coronaviruses (CoV). We conducted an evaluation of CoV in rhinolophid and vespertilionid bat species common in Europe. Rhinolophids carried severe acute respiratory syndrome (SARS)-related CoV at high frequencies and concentrations (26% of animals are positive; up to 2.4 × 108 copies per gram of feces), as well as two Alphacoronavirus clades, one novel and one related to the HKU2 clade. All three clades present in Miniopterus bats in China (HKU7, HKU8, and 1A related) were also present in European Miniopterus bats. An additional novel Alphacoronavirus clade (bat CoV [BtCoV]/BNM98-30) was detected in Nyctalus leisleri. A CoV grouping criterion was developed by comparing amino acid identities across an 816-bp fragment of the RNA-dependent RNA polymerases (RdRp) of all accepted mammalian CoV species (RdRp-based grouping units [RGU]). Criteria for defining separate RGU in mammalian CoV were a >4.8% amino acid distance for alphacoronaviruses and a >6.3% distance for betacoronaviruses. All the above-mentioned novel clades represented independent RGU. Strict associations between CoV RGU and host bat genera were confirmed for six independent RGU represented simultaneously in China and Europe. A SARS-related virus (BtCoV/BM48-31/Bulgaria/2008) from a Rhinolophus blasii (Rhi bla) bat was fully sequenced. It is predicted that proteins 3b and 6 were highly divergent from those proteins in all known SARS-related CoV. Open reading frame 8 (ORF8) was surprisingly absent. Surface expression of spike and staining with sera of SARS survivors suggested low antigenic overlap with SARS CoV. However, the receptor binding domain of SARS CoV showed higher similarity with that of BtCoV/BM48-31/Bulgaria/2008 than with that of any Chinese bat-borne CoV. Critical spike domains 472 and 487 were identical and similar, respectively. This study underlines the importance of assessments of the zoonotic potential of widely distributed bat-borne CoV.

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