Browsing M.Sc Thesis/Project by Subject "Machine Learning"
Now showing items 1-19 of 19
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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 ... -
An Adaptive Feature Selection Algorithm for Student Performance Prediction
(UIU, 2024-07-15)Educational Data Mining (EDM) is used to ameliorate the teaching and learning pro- cess by analyzing and classifying data that can be applied to predict the students’ academic performance, and students’ dropout rate, as ... -
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. ... -
Comparative Analysis of Intrusion Detection Systems and Machine Learning Based Model Analysis Through Decision Tree
(MSCSE Program, United International University, 2023-12-20) -
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 ... -
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 ... -
Early Prediction Model of Macrosomia Using Machine Learning for Clinical Decision Support
(MSCSE Program, United International University, 2024-01-05)The condition of fetal overgrowth, also known as macrosomia, can cause serious health complications for both the mother and the infant. It is crucial to identify high-risk macrosomia- relevant pregnancies and intervene ... -
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 ... -
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 ... -
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 ... -
Novel Feature Extraction for Predicting Gram-Positive and Gram-Negative Bacteria Protein Sub-cellular Localization
(2017-11-25)Protein sub-cellular localization is defined as predicting the functioning location of a given protein in the cell. It is considered an important step towards protein function prediction and drug design. In this study, we ... -
Pattern Mining From Unlabeled News Article Dataset Using Semi-Supervised Learning
(2023-03-11)Text classification is one of the prominent tasks in the field of Natural language Processing as day by day the amount of textual data is growing rapidly, Therefore it is an emergent demand to build some kind of knowledge ... -
Prediction of Protein methylation sites of lysine residues using machine learning algorithms
(2023-03-11)Post Translational Modification (PTM) plays an essential role in the biological and molecular mechanisms. They are also considered as a vital element in cell signaling and networking pathways. Among different PTMs, Methylation ... -
Subcellular Localization of Multi-class Proteins Using Label Power-set Encoding
(2018-06-30)As knowledge is essential in all research or even research initiative. Therefore, biologists always try to know where a protein resides in a cell . They can elucidate the functions of the protein with this revelation. Armed ... -
Web Application for Churn Prediction
(2022-03-30)Customers are the driving force for a business to thrive. To make a new product, decisions have to be made whether this is something which the customers will resonate with. This is why it is absolutely necessary to understand ...