NetEPD

Welcome to NetEPD

Proteins are vital organic macromolecules of cells, which are the basis material of life. They are not only the main undertakes of physiological functions, but also the direct embodiments of the phenomenon life. Up to now, many centrality methods based on network topological characteristics have bean put forward to identify essential proteins and have secured significant achievements on basis of PPIN in the form of graphic representation.

NetEPD is a very convenient web service to analyze the protein function and the essentiality of protein, which requires no configuration or installation.

First, it integrats PPI network from four database (BioGrid, DIP, MIPS and MINT), gene expression from NCBI's GEO database and subcellular localization data from COMPARTMENTS database for more accurate prediction of essential proteins from topological, temporal and spatial characteristics.

Second, the integration of computational methods, such as DC, EC, MNC and so on, for detecting essential protein is a critical part of NetEPD.

Third, it not noly evaluates prediction results with a diverse set of six evaluation measures and jackknife line diagram, but also visualizes topological structure of PPI networks with four modes.

This platform can be helpful for effective and efficient researching on essential protein. There is a tutorial for you to make batter use of NetEPD.

For ease of use, the format of the input data is shown below. If you're still confused, three dataset examples are available to you.

PPI data format

NOTICE: Enter or upload a list of identifiers which is a tab-delimited string for each row, for example:

P35202 P14164
P35202 Q04174

Or you can choose a PPI network based on the organism name which you must select firstly in the right column!

Gene expression data format

NOTICE: Enter or upload a list of identifiers which is a tab-delimited string for each row, for example:

P35202 0.55618618 0.073988438 ... ...
P35202 1.994324565 11.07745647 ... ...

Or you can choose a gene expression dataset based on the organism name which you must select firstly in the right column!

Subcellular location data format

NOTICE: Enter or upload a list of identifiers which is a tab-delimited string for each row, for example:

P35202 Cytoplasm
P35202 Nucleus

The subcellular localization information in a cell is generally classified into 11 subcellular location categories: cytoskeleton, golgi apparatus, cytosol, endosome, mitochondrion, plasma membrane, nucleus, extracellular space, vacuole, endoplasmic, reticulum, peroxisome.

Or you can choose a subcellular location dataset based on the organism name which you must select firstly in the right column!