Advancement in the field of metagenomic research have highlighted the role of microbiomes can play ecologically and clinically contexts. So, our proposed platform will provide metagenomic researchers with a friendly user ...

Recognizing subtle and implied forms of hate speech is convoluted. Fine-tuning pre-trained language models (PLMs) to generate an explanation for an incoming implicit statement has become an active area of research. Moreover, ...

Generating unit tests is a crucial undertaking in software development, demanding substantial time and e↵ort from programmers. The advent of Large Language Models (LLMs) introduces a novel avenue for unit test script ...

Intensive Care Units (ICUs) collect vast amounts of data, including patient vitals, often recorded as time series data. This data can be analyzed to extract meaningful data, which can aid in timely intervention, improving ...

This study seeks to forecast microbial colonization in the human gut and oral microbiomes by examining various factors, including diet, host genetics, and environmental influences. Through the utilization of sophisticated ...

The project introduces the development and evaluation of machine learning models incorporating both unsupervised learning clustering and supervised learning classification and regression techniques. These models aim to ...

Blood cancer has emerged as a growing concern over the past decade, necessitating early detection for timely and effective treatment. Traditional methods of diagnosing blood cancers involve a series of pathological tests ...

Drug discovery is divided into 4 phases. The first phase is in-silico processes beginning with target identification and validation, followed by the hit discovery process, assay development, high throughput screening, ...

Cardiovascular disease (CVD) remains a significant global health challenge, influenced by a complex interplay of genetic and environmental factors. Dysregulated lipid metabolism, a key contributor to CVD, disrupts cholesterol ...

The intricate nature of tumor heterogeneity and the personalized responses of cancer patients to drug treatments present significant challenges in the field of oncology. In this thesis, I aim to address such challenges by ...