5: Bioinformatics Flashcards
What is bioinformatics?
Bioinformatics is conceptualizing biology in terms of molecules (in the sense of chemistry and physics) and using informatics techniques like computational statistics to better organise and understand large biological datasets. It is a multidisciplinary field as it combines, biology, chemistry, computer science, statistics.
What are the key components of bioinformatics
Bioinformatics combines biology (the study of living systems), computer science (the development of algorithms and tools), statistics (the analysis of data), and mathematics (the modeling of biological processes) to study and interpret biological data.
What is the main goal of bioinformatics?
To understand complex biological processes by extracting meaningful insights from large-scale biological data at a molecular level.
Why is there a goal of bioinformatics?
- To gain a full insight into a biological system
- To help develop and inform on research experiments
- To facilitate the development of biotechnological applications (bioprospecting, biomimicry etc.)
- To develop better health and wellbeing knowledge and applications (medicines, diagnostics, preventatives etc)
What are some examples of bioinformatics applications?
Bioinformatics has diverse applications in genomics, proteomics, drug discovery, and personalized medicine. It is used for analyzing genomic data, predicting protein structures, analyzing gene expression patterns, comparing genomic sequences, designing drugs, and developing personalized treatment plans.
What is the central dogma of molecular biology
The central dogma of molecular biology describes the flow of genetic information within a cell. It states that DNA is transcribed into RNA and RNA is translated into proteins. This process is fundamental to understanding how genetic information is used to build and maintain living organisms.
What is DNA sequencing
DNA sequencing is the process of determining the precise order of nucleotides (A, T, C, and G) in a DNA molecule. It allows researchers to read the genetic information encoded in the DNA.
What is the purpose of DNA sequencing
DNA sequencing is used to determine the order of nucleotides in a DNA molecule. Its purpose is to identify genetic variations, mutations and other genomic features that contribute to biological processes and diseases. it helps in understanding the genetic basis of traits and diseases and enables personalised medicine approaches
What are some examples of bioinformatic analyses
Bioinformatic analyses involve methods and techniques used to study biological data computationally. Examples include identifying genetic mutations associated with diseases, predicting protein structures, analyzing gene expression patterns, comparing genomic sequences, and designing drugs based on molecular interactions.
What is the purpose of data visualization in bioinformatics?
Data visualisation in bioinformatics aims to present complex biological data in a visual and intuitive format. it helps researchers and clinicians understand patterns, relationships and trends within large datasets. Data visualisation enables effective data exploration, hypothesis generation and communication of findings to facilitate decision making
What is ClinVar
ClinVar is a public database that collects and aggregates information on genetic variations and their clinical significance. It provides a resource for researchers and clinicians to understand the relationship between genetic variants and human health conditions. ClinVar data is often used in bioinformatics analyses to interpret genomic data and identify disease-associated genetic variants.
What is the aim of expression analysis in bioinformatics
to measure and quantify gene expression levels in different experimental conditions. It involves analyzing RNA sequencing data to identify genes that are differentially expressed between samples. expression analysis helps understand gene regulation, identify biomarkers and uncover molecular mechanisms underlying diseases
What are the steps involved in expression analysis
Expression analysis typically involves steps such as alignment of sequencing reads to a reference genome, quantification of gene expression levels, normalization of expression values, and statistical analysis to identify differentially expressed genes. These steps enable the identification of genes and pathways associated with specific biological processes or conditions.
