Related Experiment Video

Updated: Jan 23, 2026

Malachite Green Assay for the Discovery of Heat-Shock Protein 90 Inhibitors
07:57

Malachite Green Assay for the Discovery of Heat-Shock Protein 90 Inhibitors

Published on: January 20, 2023

6.7K

Exploiting the application of l-aptamer with excellent stability: an efficient sensing platform for malachite green

Xiaowei Luo1, Zhifeng Chen2, Hongfeng Li2

  • 1Guangdong Provincial Key Laboratory of Construction and Detection in Tissue Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Biomaterials Research Center, School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China. jhuangaf@connect.ust.hk and Department of Chemistry, University of Washington, Washington 98195, USA.

The Analyst
|June 13, 2019
PubMed

More Related Videos

A Silicon-tipped Fiber-optic Sensing Platform with High Resolution and Fast Response09:03

A Silicon-tipped Fiber-optic Sensing Platform with High Resolution and Fast Response

Published on: January 7, 2019

7.6K
Author Spotlight: Advancements and Applications in Nanoparticle Synthesis Through Laser Ablation in Liquids06:15

Author Spotlight: Advancements and Applications in Nanoparticle Synthesis Through Laser Ablation in Liquids

Published on: June 16, 2023

2.6K

Related Concept Videos

Microsoft Excel: Plotting Mean, SD, and SE01:18

Microsoft Excel: Plotting Mean, SD, and SE

In Microsoft Excel, plotting the mean along with standard deviation (SD) and standard error (SE) helps visualize data variability and reliability. To plot these values, follow these steps:
First, calculate the mean, SD, and SE of your data. The mean is obtained using the formula `=AVERAGE(range)`, while SD can be calculated with `=STDEV.P(range)` for a population or `=STDEV.S(range)` for a sample. SE is calculated as `=SD/SQRT(n)`, where `n` is the sample size.
To plot these values, use a bar...
1.1K
Microsoft Excel: Student's t-Test01:25

Microsoft Excel: Student's t-Test

Student's t-test in Microsoft Excel is a statistical method used to compare the means of two groups to determine if they are significantly different from each other. It's commonly used to evaluate hypotheses, such as testing whether a treatment has an effect compared to a control group. Excel provides built-in functions to perform t-tests, making it accessible for users needing to conduct basic statistical analysis.
To conduct a t-test in Excel, use the T.TEST function or the "Data...
1.6K
Osmoregulation in Fishes02:32

Osmoregulation in Fishes

When cells are placed in a hypotonic (low-salt) fluid, they can swell and burst. Meanwhile, cells in a hypertonic solution—with a higher salt concentration—can shrivel and die. How do fish cells avoid these gruesome fates in hypotonic freshwater or hypertonic seawater environments?
53.0K
Microsoft Excel: Pearson's Correlation01:18

Microsoft Excel: Pearson's Correlation

Microsoft Excel is a powerful tool for statistical analysis, including calculating Pearson's correlation coefficient, which measures the strength and direction of a linear relationship between two continuous variables. Pearson's correlation coefficient, often denoted as "r," ranges from -1 to 1. A value close to 1 indicates a strong positive correlation, meaning as one variable increases, the other does too. A value close to -1 indicates a strong negative correlation, implying...
2.0K
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
1.5K
The Sense of Self: Reflected Self-Appraisal and Social Comparison02:57

The Sense of Self: Reflected Self-Appraisal and Social Comparison

According to Charles Cooley, we base our image on what we think other people see (Cooley 1902). We imagine how we must appear to others, then react to this speculation. We don certain clothes, prepare our hair in a particular manner, wear makeup, use cologne, and the like—all with the notion that our presentation of ourselves is going to affect how others perceive us. We expect a certain reaction, and, if lucky, we get the one we desire and feel good about it. But more than that, Cooley...
55.5K