A Review of Data Mining Optimization Techniques for Bioinformatics Applications

Thareja, Preeti; Chhillar, Rajender Singh

doi:10.14445/22315381/ijett-v68i10p210

Cited by 5 publications

(3 citation statements)

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“…That is why, in bioinformatics', these methods were frequently connected to class prophecy and class detection correspondingly (12). The Custom analytics tools have, consequently developed to be greatly critical in bioinformatics and it could help speeding up the research manner (13).…”

Section: Introductionmentioning

confidence: 99%

A Detailed Survey on Data Mining Based Optimization Schemes for Bioinformatics Applications

Thareja¹,

Chhillar²

2022

ECS Trans.

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In computational science paradigm, bioinformatics and the data mining approach afford specific and advocating research and development schemes. The technical science of mining, managing, and coordinating of resources retrieved from the biological sequences is known as bioinformatics. Some of the current developments, for example, genome-sequencing initiatives, micro-arrays, proteomics, functional, and the essential genomics are ought to be strapped the frontlines of human acquaintance. In recent times, the data analytics and artificial learning methods have stayed progressing in paces. This has emerged through the high-impact applications from promotion to science. The two regions obligate generally been increasing individually; even though scholars have disbursed much exertion on data mining for bioinformatics. This kind of distinctive problem objects to conduit the available gap concerning bioinformatics system and data mining techniques by unstinting exploration assimilating this two. It is believed that the data mining might deliver required tools for enhanced thoughtful of gene expression, drug strategy, and further developing complications in genomics and proteomics. This current survey provides a comprehensive analysis on data mining centered bioinformatics and its applications.

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Section: Introductionmentioning

confidence: 99%

A Detailed Survey on Data Mining Based Optimization Schemes for Bioinformatics Applications

Thareja¹,

Chhillar²

2022

ECS Trans.

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“…Heath Sector advances at a lightning pace after the adaptation of Information Technologies. The use of Predictive algorithms in Data Mining is not limited solely to informatics (1)(2)(3)(4). It has also become a part of the health sector and helps medical specialists to forecast the onsets of several conditions based on certain attributes such as age, blood pressure, level of glucose, insulin, etc.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Three Predictive Algorithms for Diabetes Mellitus Against the Pima Indians Dataset

Darolia¹,

Chhillar²

2022

ECS Trans.

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Diabetes mellitus is a metabolic disease in which the pancreas fails to produce enough insulin required for the processing of blood glucose. Most medical institutions analyze Electronic Health Records (EHRs) manually and then predict whether the patient is diabetic or not. The objective of this work is to classify diabetes and non-diabetes patients using predictive algorithms/techniques. These algorithms provide cost, time, and effort-effective solutions for the prognosis and diagnosis of diabetes mellitus. In this work, popular algorithms like Artificial Neural Network (ANN), Random Forest (RF), and Logistic Regression (LR) have been used against the PIMA Indians. Dataset and analysis has been carried out on open-source software WEKA. In addition, this paper provided state-of-the-art by various researchers related to the said topic. This work concluded that LR outperforms other algorithms, with the accuracy of 77.10%, but in the case of area under the curve (0.83), both LR and RF perform equally well.

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“…It entails the creation of analysis tools and techniques to obtain, store, retrieve, manipulate, model databases, visualization, and estimation. As a result, custom analytics tools have become extremely important in bioinformatics, and they help to speed up the research process [5]. Sequencing and annotating an individual's entire collection of DNAs, for instance, are two common tasks in biotechnology.…”

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confidence: 99%