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Related Concept Videos

Synthetic Biology02:55

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Experimental RNAi02:15

Experimental RNAi

RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
siRNA - Small Interfering RNAs02:30

siRNA - Small Interfering RNAs

Small interfering RNAs, or siRNAs, are short regulatory RNA molecules that can silence genes post-transcriptionally, as well as the transcriptional level in some cases. siRNAs are important for protecting cells against viral infections and silencing transposable genetic elements.
In the cytoplasm, siRNA is processed from a double-stranded RNA, which comes from either endogenous DNA transcription or exogenous sources like a virus. This double-stranded RNA is then cleaved by the ATP-dependent...
Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
In-vitro Mutagenesis01:16

In-vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

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Updated: Jun 18, 2026

In Silico Clinical Trials for Cardiovascular Disease
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In Silico Clinical Trials for Cardiovascular Disease

Published on: May 27, 2022

In silico biology.

Chrisantha T Fernando1, Richard A Goldstein, Phil Husbands

  • 1Department of Informatics, University of Sussex Falmer, Brighton, BN1 9RH, United Kingdom.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|November 13, 2009
PubMed
Summary
This summary is machine-generated.

Computer models are increasingly used to study life, offering new ways to explore biological phenomena. This approach allows for unprecedented examination and manipulation of complex biological systems.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Artificial Life

Background:

  • Traditional biological research focuses on existing living systems.
  • Limitations exist in studying complex biological phenomena through observation alone.

Framework:

  • Development of advanced computer models to simulate life.
  • Capturing salient aspects of biological systems computationally.

Implementation:

  • Utilizing computational models for biological research.
  • Enabling manipulation and exploration of biological phenomena.

Implications:

  • Unprecedented opportunities to investigate fundamental biological questions.
  • Advancing the field of systems biology through simulation.
  • Potential for new discoveries in understanding life.