About This Project

DZZOM transforms OMICS into intelligence with NETWORK MEDICINE solutions, and makes targeted drug/biomarker R&D cost and time efficient.

ZZOM is a biopharma focused network-sciences company. The Company has been incorporated with the mission to further develop and introduces its disruptive Network Medicine platform services throughout the entire life-cycle of drug/biomarker development and production.

Our proprietary solutions have been developed based on the scientific concepts and results validated by our academic research partners.

Network Medicine

Network Medicine is the rapidly developing field, which applies systems/computational biology and network science methods to drug/biomarker development and production. Networks can be used to visualize and analyze a broad range of biological processes, with nodes in the network representing a biological entity (e.g., gene, protein, enzyme, or disease) and edges representing the relationships between entities (e.g., physical interactions, transcriptional activation, correlations in gene expression levels). This holistic approach is used to relate the complete set of macromolecular interactions between the biological entities and their products to diseases.

Disease Network

Disease Network is novel paradigm for understanding disease expression. It is the integration of multiple types of -omics data into perturbed, dynamic networks. A Disease Module is defined as a group of network components that contribute to a cellular or organismic phenotype disruption of which leads to a particular pathophenotype. Different diseases are connected to each other by common genes. Genes associated with the same or similar diseases tend to cluster together. Modular networks emerge at many different levels, such as genes, transcripts, proteins, metabolites, organelles, cells, organs, and organ systems.

Disease Module Analysis:

DZZOM Deploys a portfolio of complex bioinformatics and network sciences tools to understand biological mechanisms by integrating, interconnecting and assessing datasets derived from multiple sources.

Identifies Disease Modules that can provide insignts into novel drug target candidates, new directions of drug repositioning or the identification of patient subgroups.

Follows a holistic approach by combining a unique set of network localization and network dynamics tools.
Overcomes major problems related to the complexity of datasets used in drug discovery, clinical development or production procedures with network approaches