Related Experiment Video

Updated: Jan 22, 2026

Production of High-Titer Infectious Influenza Pseudotyped Particles with Envelope Glycoproteins from Highly Pathogenic H5N1 and Avian H7N9 Viruses
08:10

Production of High-Titer Infectious Influenza Pseudotyped Particles with Envelope Glycoproteins from Highly Pathogenic H5N1 and Avian H7N9 Viruses

Published on: January 15, 2020

8.8K

Avian Influenza A (H7N9) and related Internet search query data in China

Ying Chen1,2, Yuzhou Zhang2, Zhiwei Xu2

  • 1School of Public Health, Sun Yat-sen University, Guangzhou, China.

Scientific Reports
|July 20, 2019
PubMed

More Related Videos

Avian Influenza Surveillance with FTA Cards: Field Methods, Biosafety, and Transportation Issues Solved12:09

Avian Influenza Surveillance with FTA Cards: Field Methods, Biosafety, and Transportation Issues Solved

Published on: August 2, 2011

19.7K
Pattern-based Search of Epigenomic Data Using GeNemo06:38

Pattern-based Search of Epigenomic Data Using GeNemo

Published on: October 8, 2017

5.4K

Related Concept Videos

How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
36.9K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
42.9K
Data Reporting and Recording01:24

Data Reporting and Recording

Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
5.4K
Data Collection I01:30

Data Collection I

Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
7.9K
Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
6.3K
Data Validation01:15

Data Validation

Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
583