DNA Sequencing with Deep Learning Technology
Project Title: Genomic Revolution: Exploring DNA Sequences with Deep Learning Technology. (Tentative)
INTRODUCTION
Deoxyribonucleic acid (DNA) is the fundamental molecule of life that encodes the genetic information of living organisms. DNA sequences are composed of four types of nucleotides: adenine (A), thymine (T), cytosine © and guanine (G). The order and arrangement of these nucleotides determine the biological functions and characteristics of different genes and genomes. DNA sequencing is the process of determining the exact order of nucleotides in a DNA molecule, which can reveal valuable insights into the molecular basis of life, health and disease.
This research aims to develop and apply novel deep-learning methods for DNA sequence analysis. Deep learning has shown remarkable success in various domains. However, its application in DNA sequence analysis is still relatively new and under-explored. This research will explore the potential and limitations of different deep learning architectures, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, bidirectional LSTM networks and self-attention networks, for various DNA sequence classification tasks, such as predicting gene functions, predictions about new DNA sequence data, detecting genetic variants and classifying species.
What is DNA Sequencing?
DNA, or deoxyribonucleic acid, is a molecule that carries most of the genetic instructions used in the growth, development, functioning, and reproduction of all known living organisms and many viruses. DNA sequences are the specific ordering of nucleotides (adenine, guanine, cytosine, and thymine) along the DNA strand. These nucleotides form the basic structural unit of DNA and are often abbreviated as A, G, C, and T.
The sequence of these nucleotides in a DNA molecule carries the genetic information of an organism. It's akin to a biological instruction manual, dictating the synthesis of proteins and other important molecules necessary for the structure and function of cells.
The order of these nucleotides in a DNA sequence is extremely important. Specific sequences of DNA nucleotides encode genes, which in turn, encode proteins. Proteins are the workhorses of the cell, performing a wide variety of tasks such as catalyzing metabolic reactions, transporting molecules, and providing structural support, among others. The unique arrangement of nucleotides in a DNA sequence is what makes each organism genetically distinct, contributing to the vast biodiversity observed in the natural world. Understanding the sequence of DNA is fundamental to many branches of biological research, including genetics, genomics, and molecular biology. Modern technologies have enabled scientists to read and interpret DNA sequences on a large scale, leading to significant advancements in fields such as personalized medicine, evolutionary biology, and the study of genetic disorders.
What is Deep Learning?
Deep learning is a type of machine learning that uses artificial neural networks to learn from data. Neural networks are inspired by the structure and function of the human brain. They are made up of interconnected nodes, each of which performs a simple mathematical operation. The nodes are arranged in layers, and the output of one layer is the input to the next layer.
Deep learning models are trained on large amounts of data. As the model is trained, it learns to identify patterns in the data. Once the model is trained, it can be used to make predictions on new data. Deep learning models have been shown to be very effective at tasks such as image recognition, natural language processing, and machine translation. They are also being used to develop new applications in a variety of fields, including healthcare, finance, and manufacturing.