SuPreMo:使用基于序列的预测模型,简化in silico扰动的计算工具
Ketrin Gjoni1,2, Katherine S Pollard1,2,3
1Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA.
bioRxiv : the preprint server for biology
|November 14, 2023
概括
预测模型的序列突变器 (SuPreMo) 能够在基因组中进行基因组编辑. 这个工具有助于优先考虑致病变体,并使用机器学习模型发现功能序列.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 计算基因组编辑至关重要,但面临着结构变异和数据输入要求的局限性.
- 现有的方法很难确定导致功能影响的特定序列变化.
结论:
- SuPreMo提供了一种用于in silico基因组序列操纵的综合解决方案.
- 由SuPreMo生成的参考对和扰乱序列可以与机器学习模型集成.
- 这种整合有助于优先考虑致病变体,并发现新的功能序列.
更多相关视频
相关概念视频
Next-generation Sequencing
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.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
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...
Golden rice
Golden rice is a genetically modified...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Methods of Medium Optimization
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...


