Shulou(Shulou.com)06/01 Report--

In this issue, the editor will bring you about how the web-based tumor biomarker gene search algorithm SurvNet is. The article is rich in content and analyzes and describes it from a professional point of view. I hope you can get something after reading this article.

SurvNet is a network-based algorithm for identifying biomarker related to the survival status of patients.

As shown in the following figure, the software needs to provide three input files

1. Network

Networ represents a network between genes, which can be an interaction network, a regulatory network, etc. The contents of the document are as follows

\ t two separate columns, each row representing two genes that interact with each other.

2. Expression

Expression represents the expression of the gene in the sample, and the contents of the document are as follows

3. Survival

Survival represents the survival status of the sample, as shown below

After the above three files are uploaded, just click Submit to run. The results are as follows

The algorithm searches the whole network for the subnet subnetwork related to the survival state of the patient, and the results are sorted according to the p value. Click the Graph button to view the subnet results, as shown below.

SurvNet provides a new algorithm for analyzing survival-related biomarker, which is the only network-based survival-related biomaker mining algorithm at present, which is worth a try.

The above is what the web-based tumor biomarker gene search algorithm SurvNet is like. If you happen to have similar doubts, you might as well refer to the above analysis to understand. If you want to know more about it, you are welcome to follow the industry information channel.

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