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Random forest for gene selection and microarray data classification

Moorthy K, Mohamad MS

Bioinformation, 2011;7(3):142-6.
PMID: 22125385

A random forest method has been selected to perform both gene selection and classification of the microarray data. In this embedded method, the selection of smallest possible sets of genes with lowest error rates is the key factor in achieving highest classification accuracy. Hence, improved gene selection method using random forest has been proposed to obtain the smallest subset of genes as well as biggest subset of genes prior to classification. The option for biggest subset selection is done to assist researchers who intend to use the informative genes for further research. Enhanced random forest gene selection has performed better in terms of selecting the smallest subset as well as biggest subset of informative genes with lowest out of bag error rates through gene selection. Furthermore, the classification performed on the selected subset of genes using random forest has lead to lower prediction error rates compared to existing method and other similar available methods.
Fulltext Breaking barriers in deployment of renewable energy

Seetharaman, Moorthy K, Patwa N, Saravanan, Gupta Y

Heliyon, 2019 Jan;5(1):e01166.
PMID: 30723834 DOI: 10.1016/j.heliyon.2019.e01166

Several economic, institutional, technical and socio-cultural barriers hinder countries from moving from the high to the low emission pathway. The objective of this research is to find out the impacts of social, economic, technological and regulatory barriers in the deployment of renewable energy. Data were collected through an online questionnaire responded to by 223 professionals working in the energy sector all over the globe. This research shows that social, technological and regulatory barriers have a strong influence on the deployment of renewable energy, while economic barriers significantly influence it indirectly. By breaking research and development-related barriers, organizations will be able to invest greatly in developing advanced technologies that can optimize usage of renewable energy and make renewable energy appear more lucrative. With less polluting and lower tariff energy solutions being made available to local people, and higher profits for manufacturers, this will create an atmosphere where all stakeholders are satisfied.
Missing-Values Imputation Algorithms for Microarray Gene Expression Data

Moorthy K, Jaber AN, Ismail MA, Ernawan F, Mohamad MS, Deris S

Methods Mol Biol, 2019;1986:255-266.
PMID: 31115893 DOI: 10.1007/978-1-4939-9442-7_12

In gene expression studies, missing values are a common problem with important consequences for the interpretation of the final data (Satija et al., Nat Biotechnol 33(5):495, 2015). Numerous bioinformatics examination tools are used for cancer prediction, including the data set matrix (Bailey et al., Cell 173(2):371-385, 2018); thus, it is necessary to resolve the problem of missing-values imputation. This chapter presents a review of the research on missing-values imputation approaches for gene expression data. By using local and global correlation of the data, we were able to focus mostly on the differences between the algorithms. We classified the algorithms as global, hybrid, local, or knowledge-based techniques. Additionally, this chapter presents suitable assessments of the different approaches. The purpose of this review is to focus on developments in the current techniques for scientists rather than applying different or newly developed algorithms with identical functional goals. The aim was to adapt the algorithms to the characteristics of the data.
Intention to reduce food waste: A study among Malaysians

Chun T'ing L, Moorthy K, Gunasaygaran N, Sek Li C, Omapathi D, Jia Yi H, et al.

J Air Waste Manag Assoc, 2021 07;71(7):890-905.
PMID: 33689567 DOI: 10.1080/10962247.2021.1900001

Malaysia, also known as a food haven, is currently facing an excessive food waste problem which poses a threat to the environment. The objective of this research is to study the factors that affect the behavioral intention of Malaysians to reduce food waste. This study employs the Theory of Planned Behavior (TPB) and the Norm Activation Model (NAM) to better understand the behavioral intention of Malaysians toward reducing food waste. A cross-sectional study was conducted, using 352 self-administered survey questionnaires. Data collected were analyzed through PLS-SEM analysis. The results show that awareness of consequences (AC) and ascription of responsibility (AR) influence personal norms, while attitude, perceived behavioral control, and personal norms (PN) have significant effect on behavioral intention (BI) to reduce food waste. Furthermore, PN partially mediates the relationship between AC and BI as well as AR and BI. This study offers critical insights which will benefit the Malaysian Government, Non-Governmental Organizations (NGOs), and other related parties in recognizing factors influencing the intention to reduce food waste which can be adopted to develop practical solutions to curb food waste in Malaysia.Implications: This study offers critical insights to the Malaysian Government, non-governmental organizations (NGOs), and other related parties in recognizing factors influencing the intention to reduce food waste which can be adopted to develop practical solutions to curb food waste in Malaysia.
Emotional intelligence on job performance: A study on Malaysian employees

Moorthy K, Juan LM, Kamarudin AA, Govindarajo NS, T'ing LC

Work, 2023;76(3):1145-1156.
PMID: 37248940 DOI: 10.3233/WOR-220418

BACKGROUND: The COVID-19 pandemic has affected the emotional intelligence of employees through the negative effects on their mental health, and led to poor workplace performance.
OBJECTIVE: The purpose of this research is to examine the level of EI of Malaysian employees in various sectors affecting their job performance through the mediating influence of psychological capital by using the Schutte Self-Report Emotional Test (SSEIT), 24-item Psychological Capital Questionnaire (PCQ-24) and Role-Based Performance Scale (RBPS) theories.
METHOD: A quantitative study was conducted. 350 sets of questionnaires were given out to Malaysian employees, of which 311 were returned. Data were analysed through regression analysis.
RESULTS: The results showed that all emotional intelligence subscales, except for utilising emotions, have a significant relationship with job performance through the effect of psychological capital.
CONCLUSION: This study offers valuable and insightful implications by combining the SSEIT, PCQ-24, and RBPS models to investigate the effect of emotional intelligence on job performance in Malaysia, which is an unusual combination model to analyse employees' job performance. It helps Malaysian companies, managers, employers, and other related parties to recognise the processes and elements that influence employees' work performance. This research also successfully developed an extended SSEIT model together with PCQ-24 and RBPS and verified their applicability on workplace performance.
Fulltext Determinants of 3Rs behaviour in plastic usage: A study among Malaysians

Chun T'ing L, Moorthy K, Yoon Mei C, Pik Yin F, Zhi Ying W, Wei Khong C, et al.

Heliyon, 2020 Dec;6(12):e05805.
PMID: 33409389 DOI: 10.1016/j.heliyon.2020.e05805

This research was conducted to explore the factors affecting Malaysians' application of reduce, reuse and recycle (3Rs) concept in plastic usage. This study adopted variables from the Theory of Planned Behaviour (TPB), namely, attitude, subjective norm and perceived behavioural control and added on two more variables, habit and facilitating conditions to study the plastic usage. Self-administered questionnaires were used to collect the data and analysis done. The results showed that all variables influence the plastic usage behaviour. This research contributes to a better understanding of the relationship between the determinants of behavioural intention of 3Rs application on plastic usage. Through the suggestions of suitable strategies, this research would contribute to reducing environment pollution caused by plastic waste.