Since understanding the molecular taxonomy of disease requires the introduction of molecular diagnostics into medical practice, molecular medicine would be a natural addition to the post-genomic era. However, current clinical practice employs only elements of molecular diagnostics, usually on the scale of single genes, while testing thousands of molecular markers for association to disease will need to employ quite new, high-throughput technologies used for sequencing, functional genomic and proteomic studies. While the sequence analysis of whole genomes is now possible, the techniques for the measurement of cellular metabolism on a genomic scale are at the early stages of development. Moreover, a vast amount of molecular information used for routine identification of molecular subclasses of disease will require new computational technologies. But even then, molecular medicine will still deal with methods for analyses of relationship between genetic background and environmental factors, underlying a disease development.

Collection, cataloging and comparison of biological data from genomes and drawing conclusions about their molecular basis are the fundamental roles of bioinformatics and systems biology. Both bioinformatics and systems biology represent the marriage of biology, mathematics, programming and data mining which offer the possibility of evolutionary analysis, description of the function and regulation of a given molecule, and also the in silico creation and simulation of molecular interactions within the genomic and proteomic networks. However, on account of the high complexity of the networks responsible for even the simplest phenotypic changes, such global analysis is still being developed. That is why real molecular medicine still needs to create new methodology for the use in medical practice which would allow to identify mechanisms governing the interdependence between genotype and phenotype.

Molecular medicine requires to expand the collection of large numbers of data sets from clinical-molecular, clinical-genetic and pharmacogenomic studies from representative populations of patients in the same stage of a disease. Like no other medical field, it will implement highly efficient methods of molecular imaging on a genomic scale and complex signaling pathway analysis by cooperation between representatives of physicians, experimental biologists and computational biologists. Such collaborative effort should create the fundaments of molecular medicine based on so-called integrative genomics.

Integrative genomics can integrate analytical data, including genetics, transcriptomics, proteomics and metabolomics in a more comprehensive manner by construction complex molecular networks to represent description of molecular phenotypes. In turn, molecular phenotypes may represent intermediate to clinically defined diseased phenotypes.

• Legal notice:
  

  Copyright (c) Pielaszek Research, all rights reserved.
  The above materials, including auxiliary resources, are subject to Publisher's copyright and the Author(s) intellectual rights. Without limiting Author(s) rights under respective Copyright Transfer Agreement, no part of the above documents may be reproduced without the express written permission of Pielaszek Research, the Publisher. Express permission from the Author(s) is required to use the above materials for academic purposes, such as lectures or scientific presentations.
  In every case, proper references including Author(s) name(s) and URL of this webpage: https://science24.com/paper/13556 must be provided.

1. Cancer genome: perspectives for the practical use of next-generation sequencing
2. Molecular medicine - Facts and myths
3. STRENGTHS AND LIMITATIONS OF INTEGRATIVE GENOMICS EXEMPLIFIED BY STUDIES OF BARRETT'S ESOPHAGUS
4. Współczesna gastroenterologia w aspekcie badań molekularnych i genetycznych - teraźniejszość i przyszłość
5. Hemochromatoza wrodzona - pilotowe badanie oceny częstości występowania w wyselekcjonowanej populacji