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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.
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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...
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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...
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Related Experiment Video

Updated: Apr 22, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
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Limits of computational biology.

Dennis Bray

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    |October 17, 2014
    PubMed
    Summary
    This summary is machine-generated.

    Scientists are far from fully understanding life's molecular processes, even in simple systems like bacterial chemotaxis. Complex biological functions in humans rely on poorly understood cellular variations, requiring more data and advanced computation.

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    Area of Science:

    • Systems Biology
    • Molecular Biology
    • Computational Biology

    Background:

    • The ability to fully reproduce life's essential aspects depends on a complete inventory of living processes.
    • Current understanding of cellular mechanisms and processes may be incomplete, posing limitations to reproduction and prediction.

    Purpose of the Study:

    • To evaluate the completeness of our current understanding of living processes, using Escherichia coli chemotaxis as a model system.
    • To identify limitations in current scientific knowledge and computational capabilities regarding cellular functions and adaptation.

    Main Methods:

    • Detailed examination of the well-understood Escherichia coli chemotaxis system.
    • Analysis of molecular uncertainty in cellular fine-tuning and adaptation.
    • Extrapolation of findings to complex biological processes in higher animals, including humans.

    Main Results:

    • Significant molecular uncertainty exists in even well-studied systems, hindering complete description and computational reproduction.
    • This uncertainty is particularly pronounced in complex processes like embryonic development, tissue homeostasis, and immune recognition in humans.
    • Vast numbers of subtle, poorly characterized cell chemistry variations underpin critical biological functions.

    Conclusions:

    • A complete inventory of living processes is not yet achievable, and many cellular mechanisms remain inaccessible.
    • Overcoming current limitations requires accumulating extensive, detailed data and developing novel computational methods for analyzing massively parallel cellular processing.
    • Understanding complex biological systems necessitates addressing the inherent molecular uncertainties and variations.