Rapidly developing next generation sequencing technologies produce vast amount of new information on effects of genomic factors on human health and their interactions with the environment. In research of rel ationships between genes and phenotypes most often used databases are NCBI, Ensembl and GeneCards. However, these databases do not cover all important information search scenarios such as interactions between genomic factors and chemically or biologically active molecules or possible genetic influences in multifac-torial diseases. Therefore, there is a need to use other database resources. The main aim of this study is to review bioinformatics databases and instruments by categorizing them into seven categories based on type of information they store and how they organize the searchable data. This review is oriented towards researchers who investigate and hypothesize links between genes and phenotypes.
Relationships between genes and disease phenotypes may be direct or complex. Direct relationship can be understood as a monogenic disease and complex as a multifactorial. It is easier to analyse genetic causes of monogenic diseases, because a causal relationship is rather obvious. However, multiple genomic regions might be associated with multifactorial disease phenotypes making analysis of these relationships more difficult. Search scenarios in these cases might be very variable and have to be performed across different resources.
In this paper we discuss 18 databases that can be used in analysis of relationships between genes and phenotypes. These da tabases con cep tually are subdivided in a following way: general databases; databases storing information about biologically active molecules and their interaction with geno-mic factors; cytogenetic databases; genome-wide association information; network and specialized databases. Researchers are introduced to existing resources aiming to help them to make an in-ormed choices best suited for their specific search scenarios. Reviewed instruments reveal different aspects of information on gene-phenotype relationships and complement each other.
