Lecture 7 - Big Data in BMS Flashcards
What is Big Data ?
Big Data refers to datasets that are too large or complex to process using traditional data processing methods.
What makes Big Data so complex to organise ?
Large volumes of data, often comprising multiple data types and substantial variation within the data make it complex to analyze.
What is the integrative analysis of different types of Big Data used for?
Integrative analysis of different types of Big Data is used to reveal interactions between variables.
What methods are used to analyze Big Data?
Computational methods and advanced statistics are used to analyze Big Data.
Who typically performs Big Data analyses?
Specialized bioinformaticians typically perform Big Data analyses.
What is the power of Big Data experiments for discovery?
Big Data experiments tend to be unbiased or hypothesis-generating, rather than hypothesis-driven, giving them huge power for discovery.
Is there a need to choose and exclude markers in advance for Big Data analysis?
No, there is no need to choose and exclude markers in advance for Big Data analysis.
What are some examples of Big Data gathered in biology?
Big Data is gathered from a large population of DNA, RNA, protein molecules, cells, tissues, organisms, etc., using techniques such as genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microscopy.
What are some areas in biology where Big Data is used to generate knowledge?
Big Data is used in biology to generate knowledge about development, physiology, drug safety and efficacy, epidemiology, disease pathobiology, understanding of past events, and prediction of future risks.
What is the aim of a transcriptomics experiment?
The aim of a transcriptomics experiment is to define the functional consequences of something, such as a drug treatment, on the expression of every gene in a biological sample.
What is the experimental strategy for a transcriptomics experiment?
The experimental strategy for a transcriptomics experiment involves extracting mRNA from a biological sample, converting it to cDNA, preparing a sequencing library, sequencing on an Illumina NGS machine, running a series of computational steps, and making statistical comparisons.
What does the volcano plot in a transcriptomics experiment represent?
The volcano plot in a transcriptomics experiment represents gene expression changes in response to a treatment or condition, with green dots representing upregulated genes and red dots representing downregulated genes.
How can gene ontology and biological pathway algorithms be used in a transcriptomics experiment?
Gene ontology and biological pathway algorithms can be used to help prioritize genes and understand the functional consequences of gene expression changes in a transcriptomics experiment.
