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Reproductive Cloning

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Reproductive cloning is the process of producing a genetically identical copy—a clone—of an entire organism. While clones can be produced by splitting an early embryo—similar to what happens naturally with identical twins—cloning of adult animals is usually done by a process called somatic cell nuclear transfer (SCNT).
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Two key frameworks are employed to analyze mass, energy, and momentum transfer: the control volume approach and the system approach. These frameworks offer different perspectives, depending on whether the focus is on a specific region in space (control volume approach) or a defined mass of fluid (system approach).
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Switching behavior in Bipolar Junction Transistors (BJTs) is a fundamental aspect utilized in various electronic circuits, particularly for digital logic applications like switches and amplifiers. In a typical switching circuit, a BJT alternates between cut-off and saturation modes, corresponding to the "off" and "on" states, respectively, thus behaving like an ideal switch.
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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
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Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
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Cloning the λ Switch: Digital and Markov Representations.

Urooj Ainuddin, Muhammad Khurram, S M Rezaul Hasan

    IEEE Transactions on Nanobioscience
    |April 5, 2019
    PubMed
    Summary

    This study models the E. coli lambda phage lysis-lysogeny switch using a finite state machine and Markov model. It reveals how to convert biological processes into computational systems for predicting bacterial cell fate.

    Area of Science:

    • Molecular Biology
    • Computational Biology
    • Systems Biology

    Background:

    • The lysis-lysogeny decision in E. coli post-lambda phage infection is a critical cellular process.
    • Key viral proteins, cI and cro dimers, regulate this switch, determining bacterial survival or death.
    • Understanding this switch is vital for molecular biology and potential therapeutic applications.

    Purpose of the Study:

    • To develop a novel computational model for the lambda phage lysis-lysogeny switch.
    • To translate complex molecular interactions into a finite state machine (FSM) framework.
    • To explore the conversion of biological processes into computing mechanisms.

    Main Methods:

    • Modeling the lysis-lysogeny switch using a finite state machine (FSM).

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  • Implementing the FSM in a field-programmable gate array (FPGA) for simulations.
  • Developing a Markov model to analyze the system's dynamics.
  • Conducting steady-state analysis on the Markov model's transition matrix.

    • Main Results:

    • Simulations were performed under random conditions to assess cell fate probabilities.
    • Steady-state analysis provided insights into the probability of lysis based on model parameters.
    • The study demonstrates the feasibility of representing biological switches computationally.

    Conclusions:

    • The developed FSM and Markov models accurately represent the lysis-lysogeny switch mechanism.
    • This approach offers a pathway for converting biological processes into computational models.
    • The findings contribute to understanding bacterial infection dynamics and computational biology.