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Circadian Rhythms and Gene Regulation

Circadian Rhythms and Gene Regulation

The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent...

Sinusoidal Sources

Sinusoidal Sources

Direct current (DC) refers to an electric current that flows in a single direction, maintaining a constant polarity. This is in contrast to alternating current (AC), which periodically changes its direction and magnitude. AC forms the backbone of modern electricity transmission and distribution systems due to its efficient long-distance transmission capabilities.
In homes, the power supplies use sinusoidal sources to provide electricity. These sources generate a voltage that varies sinusoidally...

Simplified Synchronous Machine Model

Simplified Synchronous Machine Model

The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...

Graphical and Analytic Representation of Sinusoids

Graphical and Analytic Representation of Sinusoids

Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...

Design Example: Underdamped Parallel RLC Circuit

Design Example: Underdamped Parallel RLC Circuit

Consider designing an oscillator circuit, a crucial component in various electronic devices and systems. The objective is to create an oscillator circuit with specific characteristics: a damped natural frequency of 4 kHz and a damping factor of 4 radians per second. To accomplish this, a parallel RLC circuit is employed, known for its ability to sustain oscillations at a resonant frequency. In this case, the damping factor is pivotal in achieving the desired performance.
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BIBO stability of continuous and discrete -time systems

BIBO stability of continuous and discrete -time systems

System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....

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相关实验视频

Updated: Jun 29, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

从生物数据到使用SINDyy的振荡器模型.

Bartosz Prokop¹, Lendert Gelens¹

¹Laboratory of Dynamics in Biological Systems, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.

|March 25, 2024

概括

此摘要是机器生成的。

这项研究揭示了SINDy算法对生物数据的局限性,包括分辨率,噪声和维度. 提出了一份逐步指南,以改善从生物振荡中推断数学模型的推理.

关键词:

生物信息学是一种生物信息学.机器学习机器学习

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Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

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Published on: June 9, 2023

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A Computational Method to Quantify Fly Circadian Activity

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Published on: October 28, 2017

科学领域:

系统生物学系统生物学
计算生物学计算生物学
生物物理学的生物物理.

背景情况:

细胞过程如分裂和昼夜节律依赖于分子振荡.
数学建模对于理解这些生物节奏至关重要.
数据驱动的方法,如SINDy (非线性动态的精细识别),为模型识别提供了强大的工具.

研究的目的:

研究将SINDy算法应用于实验生物振荡数据的约束和局限性.
系统地分析数据分辨率,噪声,维度和先前知识对SINDy性能的影响.
开发一个实用指南,用SINDy. 来从生物数据中推断数学模型.

主要方法:

将SINDy算法直接应用于不同复杂度和维度的各种通用振荡器模型.
对包括数据分辨率,噪声水平和维度在内的因素进行系统分析.
使用实验性酵母糖解振荡数据验证拟议的建模方法.

主要成果:

确定数据分辨率不足,高噪声水平,高维度和有限的先前知识是SINDy在生物环境中的关键限制.
证明了这些因素对模型推理准确性的系统影响.
成功验证了在真实生物数据上进行模型推理的指导方法.

结论:

SINDy算法对生物模型识别有前途,但需要仔细考虑数据质量和实验设计.
要克服SINDy在复杂的生物系统中应用的局限性,需要采用结构化的方法.
拟议的指南有助于从实验振荡数据中发现更强大,更准确的数学模型.