The Human Proteome Survey Database (HumanPSDTM) is a catalog of proteins and their complexes from human cells, plus their orthologs from mouse and rat sources.
Its main focus is on the association of human proteins with diseases as well as on their potential use as biomarkers.

Drugs targeting human proteins are reported. In addition, information can be retrieved on the molecular functions, biological roles, localization, and modifications of proteins, expression patterns across cells, tissues, organs, and tumors, consequences of gene mutations in mice, and the physical and regulatory interactions between proteins and genes. The TRANSPATH® database on signal transduction and metabolic pathways is an integral part of HumanPSDTM.

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Contents of a standard locus report of HumanPSD

Biomarker Associations
Diseases associated with MYC
Inherit MYC mutations
Drug Interactions
Drug(s) targeting MYC
Gene Ontology
Molecular function
Biological process
Cellular component
Tissue expression

Regulation of MYC expression

Mutant Phenotype

Mutant phenotype of closely related homolog(s)

Pathways & interactions
Protein-protein interactions
Events acting on MYC
Events triggered by MYC
Transcriptional Regulation
Add a subscription to TRANSFAC® and this report will display additional information
RNA Features
Overview of RNA sequence
Protein Features
Overview of protein sequence and structure
Post-translational modifications of MYC protein
View complex containing MYC protein
Accessions mapped to this record
Editor’s Notes
Disease related

Biomarker / disease associations

A tabular summary of literature-derived relationships between human genes and gene products with human diseases is given.
These associations are clearly sorted according to their type, e.g. whether a gene/protein has a causal relationship with a disease to develop, or whether it is merely correlative, etc.
Disease association MYC

Tabulated summary of disease associations of the human MYC gene.

Key features

Reports about more than 53,000 proteins and 5000 microRNAs.
More than 132,000 gene-disease assignments extracted from original scientific literature and evaluated by experts, referring to more than 3,900 diseases (human) or disease models (mouse).
More than 51,000 drug-protein interactions, referring to more than 9,200 drugs.
More than 600,000 assignments to Gene Ontology (GO), manually annotated and quality-checked.
More than 2,361,000 gene expression assignments.
More than 958,000 annotation statements given.
More than 385,000 references to peer-reviewed scientific publications provided.
An integrated Ontology Browser supports easy selection of defined sets of gene/molecules.
A tool for functional analysis allows to identify shared characteristics in a set of genes/proteins or miRNAs.
TRANSPATH included!


Quickly access detailed reports for individual genes, proteins, miRNAs, diseases,
and drugs without time-consuming literature search.
Uncover biologically relevant connections between seemingly disparate genes,
diseases, and drugs.
Identify and rank potential therapeutic targets based on known functional
Explore canonical pathways and build custom protein networks, overlaying
known disease and drug associations.


Drug report and pathway report in HumanPSD+TRANSPATH® – this video demonstrates how drug report looks like in the online interface of HumanPSD+TRANSPATH® database. Target molecules, corresponding to a particular drug, are demonstrated, and pathways, in which these molecules are involved, are shown in a very detailed way, with all the underlying reactions, from which the corresponding pathways are constructed. Clinical trials info is also shown for each particular drug and for certain cases even metabolizing enzymes and associated pathways info is also available.

Disease report overview in HumanPSD+TRANSPATH®this video demonstrates how disease report looks like in the online interface of HumanPSD+TRANSPATH® database. Disease biomarkers are shown (genes or proteins or miRNAs) with the type of association and type of indication info. All respective references are demonstrated. Disease similarity maps are also shown (these maps are based on the similarity of different diseases in respect to the common biomarkers that they share).

Disease similarity maps by common biomarkers in HumanPSD+TRANSPATH® – this video shows the overview of disease similarity maps. Common biomarkers of different diseases are displayed on these schemas. The searched disease is placed in the center of the map. The maps have the following color code: diseases sharing common biomarkers are connected with red lines; diseases that have ontological relationships according to the MeSH ontology are connected by gray lines.


Current HumanPSD™ release

HumanPSD™ release 2022.1

The Human Proteome Survey Database (HumanPSDTM) with focus on human proteins as disease biomarkers and drug targets contains these new features:

  • Quantitative tissue expression diagram in human locus reports

Normalized transcript expression levels from Human Protein Atlas (v20) are displayed in a histogram across 61 different cell types / tissues. There are several sorting and grouping options, e.g. cell/tissue by organ. In addition, a value for the relative tissue specificity as indicator for expression ubiquity of the respective human gene is given.

  • Extended options to use search results as input for further queries

The added options include the possibilities to query for drugs approved or under research for a certain condition from a search result of diseases and vice versa.

  • Biomarker and drug target data update

The number of disease annotations increased to 369,215 and the number of unique gene/biomarker – disease assignments to 126,804. Targets for FDA – approved drugs have been added by manual curation and the number of drug – target protein associations is now 51,827.

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            The basic information unit is a “locus report”, which summarizes the existing knowledge about the product(s) of a gene. It is part of a hierarchy, with individual proteins (isoforms such as splice variants) encoded by a gene at a level under the locus report, and summarizing features of the orthologs of human, mouse and rat origin at a higher level.

            Information downloads

            HumanPSDTM Statistics (download)
            HumanPSDTM Features (download)
            HumanPSD FlyerTM (download)



            Stegmaier, P., Krull, M., Voss, N., Kel, A.E., Wingender, E. (2010) Molecular mechanistic associations of human diseases. BMC Syst Biol. 4, 124. doi: 10.1186/1752-0509-4-124. PubMed.

            Michael, H., Hogan, J., Kel, A., Kel-Margoulis, O., Schacherer, F., Voss, N., Wingender, E. (2008) Building a knowledge base for systems pathology. Brief. Bioinform. 9, 518-531. doi: 10.1093/bib/bbn038. PubMed.

            Wingender, E., Crass, T., Hogan, J.D., Kel, A.E., Kel-Margoulis, O.V., Potapov, A.P. (2007) Integrative content-driven concepts for bioinformatics “beyond the cell”. J Biosci. 32, 169-180. PubMed.

            Hodges PE, Carrico, P.M., Hogan, J.D., O’Neill, K.E., Owen, J.J., Mangan, M., Davis, B.P., Brooks, J.E., Garrels, J.I. (2002) Annotating the human proteome: the Human Proteome Survey Database (HumanPSD) and an in-depth target database for G protein-coupled receptors (GPCR-PD) from Incyte Genomics. Nucleic Acids Res. 30:137-141. PubMed.

            HumanPSD is a trademark of QIAGEN GmbH.