Browsing School of Science and Engineering (SoSE) by Subject "Machine Learning"
Now showing items 1-20 of 28
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Accurately Predicting Microbial Phosphorylation Sites Using Evolutionary and Structural Features
(2022-11-11)Post-translational modification (PTM) is a biological process involving a protein’s enzymatic changes after its translation by the ribosome. Phosphorylation is one of the most critical PTMs that occurs when a phosphate ... -
Analysis of Gene Expression Data forGlioma Grade Classification andSurvival Time Prediction
(2020-08-16)A glioma is a sort of tumor that begins in the glial cells of the brains or the spine. Gliomas contain around 30 percent of all brain tumors and focal sensory system tumors and 80 percent of all dangerous brain tumors. ... -
Application of Machine Learning Algorithms to Identify Recombination Spots
(2019-09-24)Meiotic recombination is a mechanism by which a cell promotes correct segregation of homologous chromosomes and repair of DNA damages. But it does not occur randomly across the whole genome. Relatively high frequencies ... -
Big Data Mining in the Presence of Concept Drifting
(2019-03-05)Concept drift in big data mining is an absolute, highly demanding research issue in this digital era. A concept in "concept drift" involved in the field of data mining (DM) and machine learning (ML) studies is referred ... -
Convolutional Neural Networks with Image Representation of Amino Acid Sequences for Protein Function Prediction
(2021-12)Proteins are one of the most important molecules that govern the cellular processes in organisms. Various functions of the proteins are of paramount importance to understand the basics of life. Several supervised learning ... -
Correlation Based Feature Selection with Clustering for Multi-Class Classification Tasks
(2019-05-20)In recent times high dimensional data is increasing rapidly. Reduce the dimensionality has become popular by feature selection process. So many scientists prefer to use correlation base feature selection method for grouping ... -
DeepDBP:A Novel Prediction Method for Identification of DNA-binding Protein Using Deep Neural Networks
(2019-03)DNA-Binding proteins are associated with many cellular level functions which includes but not limited to body’s defense mechanism and oxygen transportation. They bind DNAs and interact with them. In the past DBPs were ... -
DNA Binding Protein Identification Using HMM Profile
(2018-02-06)DNA-binding proteins play important role in various processes within the cell.Various machine learning classification algorithms and feature extraction techniques have been used to solve this computational problem of ... -
Enhanced prediction of A-to-I RNA editing sites using nucleotide compositions
(2019-08-31)RNA editing process like Adenosine to Intosine (A-to-I) often influences basic functions like splicing stability and most importantly the translation. Thus knowledge about editing sites is of great importance in molecular ... -
Event Detection and Violence Recognition from Textual News through Multilayer Perceptron and Supervised Learning
(2018-11)An unprecedented way is accomplished by using concept words derived from statistical context analysis between sentences which is better than traditional methods that use only keyword representation. Through scaling to a ... -
A Feature Group Weighting Method for Classifying High-Dimensional Big Data
(2019-11-25)Features hold the distinctive characteristics and intrinsic values of data. But it's of no use if the important information and pattern can not be extracted from the data coming from disparate sources and applications. ... -
Feature Selection Method for DNA-Binding Protein Identification
(2017-12-03)DNA-binding proteins play a very important role in the structural composition of the DNA. In addition to that they regulate and effect various cellular processes like transcription, DNA replication, DNA recombination, ... -
Identification of Bacterial Sigma 70 Promoter Sequences Using Feature Subspace Based Ensemble Classifier
(2018-09-24)Sigma promoter sequences in bacterial genomes are important due to their role in transcription initiation. Sigma70 is one of the most important and crucial sigma factors. In this paper, we address the problem of identification ... -
Identifying Sigma 70 Promoters Using Multiple Windowing and Optimal Features
(2018-09-24)In bacterial DNA, there are specific sequences of nucleotides called promoters that can bind to the RNA polymerase. Sigma70 (σ 70) is one of the most important promoter sequences due to it’s presence in most of the DNA ... -
Improving Machine Learning Methods for Handling Data Imbalance Problem
(2022-07)Class unbalanced datasets are widespread in various fields, including health, security, and banking. When dealing with imbalanced datasets, a standard supervised learning algorithm is biased toward the dominant class. In ... -
Machine Learning for Mining Big Data: A Review
(2018-11-24)Development of Big Data is virtually transforming our lifestyle. It is also accelerating industrial growth through process optimization, insight discovery and improved decision making. The massive scale of big data exceeds ... -
Machine Learning for Mining Big Data: A Review
(2018-11-20)Development of Big Data is virtually transforming our lifestyle. It is also ac- celerating industrial growth through process optimization, insight discovery and improved decision making. The massive scale of big data exceeds ... -
Network Intrusion Classification Employing Machine Learning: A Survey
(2019-01-18)In this modern era computer network security is a vital issue. Network security is developed by an efficient Intrusion Detection System (IDS). It is used to identify unauthorized access, malicious attacks and give an alert ... -
Novel Class Detection in Concept Drifting Data Streams Using Decision Tree Leaves
(2018-10-24)Concept drifting data streams often occurs in weather forecasting, intrusion detection and other applications. One of the difficulties with handling concept drifting data streams is the existence of novel classes in the ... -
A Novel Approach to Predict the Origin of Replication
(2021-01-15)In the genome of every species, there exists an origin, known as the origin of replication (ORI), from where the genome starts to replicate itself during the process of cell division. Finding out this origin; is therefore ...