登录查看更多内容

What are the most effective ways to select controls for a biotech experiment?

由人工智能和领英社区提供技术支持

Biotechnology is a field that relies on experiments to test hypotheses, develop products, and solve problems. However, not all experiments are equally valid, reliable, or reproducible. One of the key factors that affects the quality of a biotech experiment is the selection of controls. Controls are samples or conditions that are used to compare with the experimental group and eliminate confounding variables. In this article, you will learn what are the most effective ways to select controls for a biotech experiment, and why they are important for your results.

此文章中的业界达人

由社区从 3 条内容中精选。了解更多

Muhammad Ali

Graduate Student @ NYU | Fulbrighter??| Computational Aging Research ??
Damian Toczyd?owski

Breaking the Code of Life via Epigenomics & Functional Genomics ?? Pioneering The Future of Epigenetics ?? Scientist ??…

1 Types of controls

When conducting a biotech experiment, there are various types of controls that you can use depending on the purpose and design of your study. Negative controls are samples or conditions that are expected to show no effect or response to the experimental treatment. For example, if you're testing the effect of a drug on cell growth, a negative control would be a cell culture without the drug. Positive controls are samples or conditions that should demonstrate a known effect or response to the experimental treatment. For instance, if you're testing the effect of a drug on cell growth, a positive control would be a cell culture with a drug known to stimulate or inhibit cell growth. Internal controls are samples or conditions included within the experimental group to account for variability and measurement errors. For example, if you're measuring gene expression using PCR, an internal control would be a reference gene expected to have constant expression levels across all samples. Finally, external controls are samples or conditions obtained from an independent source or protocol to validate the experimental method and data. If you're measuring gene expression using PCR, an external control would be a standard curve or positive control from a previous experiment.

添加您的观点

Muhammad Ali

Graduate Student @ NYU | Fulbrighter??| Computational Aging Research ??
举报内容
A negative control, in essence, is the exact opposite of the treatment condition. To completely eliminate confounding factors (as much as possible), it's important to process negative controls in the exact same way - and the exact same time, if they are for time-sensitive experiment - as the treatment groups. For instance, if you are measuring the effect of different diets on two groups of mice, it's important to ensure that both mice receive the diet at the exact same time. If there are so many mice that it takes you 30 minutes to feed the control group and another 30 to feed the treatment group, their circadian cycles may confound any differences that you observe - which you may believe stem from the diet.

已翻译

赞

2 Criteria for selecting controls

When selecting controls for your biotech experiment, you should take into account criteria such as relevance, adequacy, and replicability. The controls should be relevant to the research question and the experimental treatment, mimicking the experimental group as closely as possible. Adequacy is also important, as the controls should have a clear and predictable outcome that can be compared to the experimental group. Additionally, the controls should be replicable and consistent across different experiments and conditions, having a low variability and a high accuracy. For example, if you are testing the effect of a drug on cell growth, the negative control should show no change in cell growth, and the positive control should show a significant change in cell growth, in the same direction as the expected effect of the experimental drug. If you are measuring gene expression using PCR, the internal control should have a stable expression level across different samples and runs, and the external control should have a reliable and reproducible standard curve or positive control.

添加您的观点

3 Benefits of using controls

Using controls in your biotech experiment can have several benefits for your results and conclusions, such as validity, reliability, and reproducibility. For example, if you are testing the effect of a drug on cell growth, controls can help you confirm that your drug is active and that your cell counting method is precise and consistent. Controls can also help reduce the impact of confounding variables and sources of error that can affect your results and interpretation. Additionally, they can provide a reference point and a standard protocol that can be repeated by other researchers to increase the reproducibility of your results and conclusions.

添加您的观点

Damian Toczyd?owski

Breaking the Code of Life via Epigenomics & Functional Genomics ?? Pioneering The Future of Epigenetics ?? Scientist ?? Epigeneticist & Geneticist
举报内容
The core tenet of scientific methodology is the indispensable presence of control in your experimental setup. Without integrating controls, results become wholly uninterpretable and unreliable. Period.

已翻译

赞

4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

添加您的观点

Damian Toczyd?owski

Breaking the Code of Life via Epigenomics & Functional Genomics ?? Pioneering The Future of Epigenetics ?? Scientist ?? Epigeneticist & Geneticist
(已编辑)
举报内容
Controls play a crucial role in experiment accuracy, especially in functional genomics aiming to understand gene functions/regulation. Well-chosen controls are key for experiment success and accurate interpretations. In genomics, controls help distinguish "true" mutations from false positives, for instance. What's an example of control? Examining both healthy and affected tissues (tumour) from the same cancer patient serves as a valuable control, next to the fully healthy individual control. The experimental design factors often includes randomization, having replicates of control & experimental group, blinding. Negative controls help underscoring unexpected effects, while positive ones may validate anticipated results.

已翻译

赞

Biotechnology

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

查看全部

What are the most effective ways to select controls for a biotech experiment?

1

2

3

4

1 Types of controls

2 Criteria for selecting controls

3 Benefits of using controls

4 Here’s what else to consider

Biotechnology

给文章评分

感谢您的反馈

更多Biotechnology相关文章

更多相关阅读内容