Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Nachol Chaiyaratana"'
Publikováno v:
Evolutionary Bioinformatics, Vol 18 (2022)
Background: Coding and non-coding short tandem repeats (STRs) facilitate a great diversity of phenotypic traits. The imbalance of mononucleotide A-repeats around transcription start sites (TSSs) was found in 3 mammals: H. sapiens, M. musculus , and R
Externí odkaz:
https://doaj.org/article/9a8538822c7c49249e89ef11a37d7bd0
Publikováno v:
IEEE Access, Vol 4, Pp 5570-5578 (2016)
For every simple connected graph, we present a polynomial time algorithm for computing a numerical index, which is composed of primary and secondary parts. Given a graph G = (V, E) where V and E are, respectively, vertex and edge sets, the primary pa
Externí odkaz:
https://doaj.org/article/ecbc46c628c04002901defcac51b26df
Autor:
Atik Sangasapaviliya, Torpong Thongngarm, Wanna Thongnoppakhun, Aree Jameekornrak, Nachol Chaiyaratana, Chanin Limwongse, Orathai Jirapongsananuruk
Publikováno v:
Asian Pacific Journal of Allergy and Immunology.
Background Most of the asthma susceptibility genes have demonstrated moderate effect. Gene-gene interaction may play a role in asthma. Objective To investigate the genetic and gene-gene interaction effects of single nucleotide polymorphisms (SNPs) in
Publikováno v:
IEEE Access, Vol 4, Pp 5570-5578 (2016)
For every simple connected graph, we present a polynomial time algorithm for computing a numerical index, which is composed of primary and secondary parts. Given a graph $G=(V,E)$ where $V$ and $E$ are, respectively, vertex and edge sets, the primary
Autor:
Piyapat Pin-on, Nachol Chaiyaratana, Apiwat Mutirangura, Chatchawit Aporntewan, Viroj Boonyaratanakornkit, Monnat Pongpanich
Publikováno v:
Nucleic Acids Research
A-repeats are the simplest form of tandem repeats and are found ubiquitously throughout genomes. These mononucleotide repeats have been widely believed to be non-functional ‘junk’ DNA. However, studies in yeasts suggest that A-repeats play crucia
Autor:
Chanin Limwongse, Theera Piroonratana, Waranyu Wongseree, Chompunut Kanjanakorn, Damrongrit Setsirichok, Monchan Sirikong, Nuttawut Paulkhaolarn, Nachol Chaiyaratana, Touchpong Usavanarong
Publikováno v:
Biomedical Signal Processing and Control. 7:202-212
This article presents the classification of blood characteristics by a C4.5 decision tree, a naive Bayes classifier and a multilayer perceptron for thalassaemia screening. The aim is to classify eighteen classes of thalassaemia abnormality, which hav
Autor:
Nalinee Mukdasanit, Tawan Wasanapradit, Thongchai Rohitatisha Srinophakun, Nachol Chaiyaratana
Publikováno v:
Korean Journal of Chemical Engineering. 28:32-40
This paper proposes a method for solving mixed-integer nonlinear programming problems to achieve or approach the optimal solution by using modified genetic algorithms. The representation scheme covers both integer and real variables for solving mixed
Autor:
Wanna Thongnoppakhun, Nachol Chaiyaratana, Monchan Sirikong, Chanin Limwongse, Anunchai Assawamakin, Theera Piroonratana, Waranyu Wongseree, Chompunut Kanjanakorn, Nuttawut Paulkhaolarn
Publikováno v:
Chemometrics and Intelligent Laboratory Systems. 99:101-110
This article presents an application of a neural network and decision trees in thalassaemia screening. The aim is to classify thirteen classes of thalassaemia abnormality and one control class by inspecting the distribution of multiple types of haemo
Autor:
Chanin Limwongse, Saravudh Sinsomros, P. Youngkong, Anunchai Assawamakin, Nachol Chaiyaratana, Pa-thai Yenchitsomanus
Publikováno v:
IEEE Engineering in Medicine and Biology Magazine. 28:25-31
This paper presents a non-parametric classification technique for identifying a candidate bi-allelic genetic marker set that best describes disease susceptibility in gene-gene interaction studies. The developed technique functions by creating a mappi
Autor:
Nachol Chaiyaratana, Suthat Fucharoen, Pranee Winichagoon, Kanjana Vichittumaros, Waranyu Wongseree
Publikováno v:
Information Sciences. 177:771-786
This paper presents the use of a neural network and a decision tree, which is evolved by genetic programming (GP), in thalassaemia classification. The aim is to differentiate between thalassaemic patients, persons with thalassaemia trait and normal s