The MorbidGenes panel: a monthly updated list of diagnostically relevant rare disease genes derived from diverse sources

The MorbidGenes panel is an open and comprehensive overview of diagnostically relevant rare disease genes based on a diverse set of resources. The panel is updated monthly to keep up with the ever increasing number of rare disease genes.

Authors

Institutions

Publication Details

Journal
Human Genetics
Published
2024-10-28
DOI
https://doi.org/10.1007/s00439-024-02711-z
Citations
2
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
1.10

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The MorbidGenes panel: a monthly updated list of diagnostically relevant rare disease genes derived from diverse sources

Konrad Platzer, Robin‐Tobias Jauss, Jasmin Bachmann, Bernt Popp et al.
2 citations
Human Genetics
Genomics and Rare Diseases
1.10
article

The MorbidGenes panel: a monthly updated list of diagnostically relevant rare disease genes derived from diverse sources

Konrad Platzer, Robin‐Tobias Jauss, Jasmin Bachmann, Bernt Popp, Rami Abou Jamra
article en
2 citations

Abstract

The MorbidGenes panel is an open and comprehensive overview of diagnostically relevant rare disease genes based on a diverse set of resources. The panel is updated monthly to keep up with the ever increasing number of rare disease genes.

Human GeneticsVol. 143(12)
Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Leipzig University (DE)
Universität Leipzig
Openalex Percentile: Top 18%
Genomics and Rare Diseases
1.10
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.