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Related Concept Videos

Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
Incomplete Dominance01:43

Incomplete Dominance

Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Related Experiment Video

Updated: Jun 8, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Data integration in genetics and genomics: methods and challenges.

Jemila S Hamid1, Pingzhao Hu, Nicole M Roslin

  • 1Biostatistics Methodology Unit, The Hospital for Sick Children Research Institute, 555 University Avenue, Toronto, ON, Canada M5G 1X8.

Human Genomics and Proteomics : HGP
|October 16, 2010
PubMed
Summary
This summary is machine-generated.

Integrating diverse genomic and proteomic data is crucial for understanding biological functions. This study proposes a conceptual framework and reviews statistical methods for effective data fusion in genomics and proteomics research.

Related Experiment Videos

Last Updated: Jun 8, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Area of Science:

  • Genomics and Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Rapid technological advances generate diverse genomic and proteomic data (gene expression, SNP, CNV, PPIs).
  • Each data type offers complementary views of the genome, but comprehensive understanding requires integration.
  • Data integration is vital for combining high-throughput genomic data with clinical, environmental, and demographic information.

Purpose of the Study:

  • To propose a conceptual framework for integrating genetic, genomic, and proteomic data.
  • To capture fundamental aspects of data integration and key steps in data fusion.
  • To review common statistical methods for combining genomic data.

Main Methods:

  • Development of a conceptual framework for genetic, genomic, and proteomic data integration.
  • Review of current statistical methods and approaches for genomic data combination.
  • Focus on data fusion techniques in genomics and proteomics.

Main Results:

  • A proposed conceptual framework for effective data integration in genomics and proteomics.
  • Identification and review of commonly used statistical methods for genomic data fusion.
  • Highlighting the importance of data integration for a holistic understanding of biological systems.

Conclusions:

  • A defined framework enhances the understanding and application of data integration in biological research.
  • Statistical methods are essential for successfully combining diverse genomic and proteomic datasets.
  • Data integration is key to advancing research in genomics, proteomics, and personalized medicine.