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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

98.8K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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Fault Types01:18

Fault Types

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When analyzing a single line-to-ground fault from phase A to ground at a three-phase bus, it is important to consider the fault impedance. This impedance is zero for a bolted fault, equal to the arc impedance for an arcing fault, and represents the total fault impedance for a transmission-line insulator flashover. To derive sequence and phase currents, fault conditions are translated from the phase domain to the sequence domain.
For line-to-line faults occurring between phases B and C, the...
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Transcription01:10

Transcription

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Overview
Transcription is the process of synthesizing RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in the proper synthesis of messenger RNA (mRNA). Regulation of transcription is responsible for the differentiation of all the different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds...
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Eukaryotic Transcription Inhibitors01:52

Eukaryotic Transcription Inhibitors

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Certain biochemical processes, such as embryonic development and cell growth regulation, depend on the repression of specific genes. DNA binding proteins known as eukaryotic transcription inhibitors regulate the repression of gene expression in eukaryotes. The presence of these inhibitors at the required location and time in the cell is triggered by the presence of hormones and additional signals from other cells.
Eukaryotic transcription inhibitors usually contain two distinct domains, a...
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Master Transcription Regulators02:23

Master Transcription Regulators

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Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
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Eukaryotic Transcription Activators02:42

Eukaryotic Transcription Activators

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Transcription activators are proteins that promote the transcription of genes from DNA to RNA. In most cases, these proteins contain two separate domains ‒ a domain that binds to DNA and a domain for activating transcription; however, in some cases, a single domain is responsible for both binding and activation of transcription, as seen in the glucocorticoid receptor and MyoD.
The binding domains are capable of recognizing and interacting with regulatory sequences on the DNA. These...
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Optimal Fault Detection and Diagnosis in Transcriptional Circuits Using Next-Generation Sequencing.

Arghavan Bahadorinejad, Ulisses M Braga-Neto

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |April 4, 2018
    PubMed
    Summary

    This study introduces a new method for detecting and diagnosing faults in biological systems using transcriptomic data. The approach accurately identifies system errors without prior fault knowledge, crucial for understanding diseases like cancer.

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    Area of Science:

    • Systems Biology
    • Computational Biology
    • Genomics

    Background:

    • Stochastic Boolean dynamical systems are crucial for modeling biological networks.
    • Observing these systems indirectly via transcriptomic data presents challenges for fault detection.
    • Next Generation Sequencing (NGS) provides valuable, albeit noisy, transcriptomic measurements.

    Purpose of the Study:

    • To develop a model-based methodology for fault detection and diagnosis in stochastic Boolean dynamical systems.
    • To enable indirect observation analysis using single time series of transcriptomic data.
    • To address the need for robust fault identification in complex biological networks.

    Main Methods:

    • Utilizing an innovations filter based on the Boolean Kalman Filter (BKF) for optimal state estimation and fault detection.
    • Implementing a fault diagnosis step using a multiple model adaptive estimation (MMAE) method with a bank of BKFs.
    • Assessing performance using false detection rates, misdiagnosis rates, and detection/diagnosis times.

    Main Results:

    • The proposed methodology effectively detects and diagnoses faults in stochastic Boolean dynamical systems.
    • The Boolean Kalman Filter (BKF) proves effective for state estimation in indirectly observed systems.
    • Numerical experiments on a p53-MDM2 network demonstrate the method's efficacy in identifying stuck-at faults.

    Conclusions:

    • The developed methodology offers a robust framework for fault detection and diagnosis in complex biological systems.
    • This approach is particularly relevant for analyzing transcriptomic data from Next Generation Sequencing (NGS).
    • The findings have implications for understanding molecular events in diseases such as cancer.