The field of Artificial Intelligence (AI) is complex and rich in specialized terminology. Creating a glossary is key to the common understanding of terms and concepts, especially in the area of sequence alignment. Below, we present a glossary with the most relevant terms:
Artificial Intelligence (AI)
It is the discipline within science focused on building systems capable of performing tasks that require intelligence when carried out by humans. It involves learning, reasoning, perception, understanding of natural language, and, in many cases, the ability to move and manipulate objects.
Sequence Alignment
A bioinformatic process used to align two or more DNA, RNA, or protein sequences to identify regions of similarity that may result from functional, structural, or evolutionary relationships among the sequences.
Algorithm
In terms of AI and computing, an algorithm is a finite sequence of well-defined instructions or steps to perform a task or solve a problem.
Machine Learning
A subfield of AI that focuses on the development of systems capable of learning and improving from experience without being explicitly programmed to do so.
Deep Learning
This is a machine learning technique that trains computers to do what comes naturally to humans: learn by example. It is based on the use of artificial neural networks with multiple processing layers.
Neural Networks
Computational models inspired by the human brain’s functioning that are capable of learning tasks by being trained with large volumes of data.
Supervised Learning
A machine learning method where the model is trained on a dataset that already contains the desired answers, known as labels.
Unsupervised Learning
A machine learning technique in which the model works with unlabeled information and must discover the structure and relationships within the data set on its own.
Reinforcement Learning
A branch of machine learning in which agents make decisions and learn based on the rewards or penalties resulting from their actions.
Natural Language Processing (NLP)
An interdisciplinary field focused on the interaction between computers and human natural languages. It deals with the understanding, interpretation, and generation of human language by machines.
Computational Genomics
A discipline that combines molecular biology and computational sciences to understand the structure, function, and evolution of genomes.
BLAST (Basic Local Alignment Search Tool)
A sequence alignment tool that finds regions of local similarity between sequences. It is used to infer functional and evolutionary relationships.
HMM (Hidden Markov Models)
Statistical models used to describe the evolution of sequential processes over time, such as time series or DNA chains.
Clustering
A technique used in unsupervised learning that allows grouping a set of objects in such a way that the objects in each group are more similar to each other than to those in other groups.
Backpropagation
A key algorithm used in the training of artificial neural networks. It facilitates the efficient calculation of the gradients necessary to adjust the network’s weights during learning.
Precision and Recall
Precision refers to the fraction of positive identifications that are truly positive, while recall is the fraction of total positives that were correctly identified.
These fundamental terms provide a solid foundation to delve into the field of sequence alignment and AI applied to bioinformatics. Knowledge of these concepts is crucial for professionals in the industry and facilitates communication across different disciplines allowing collaborative advancement in science.
