DiseaseLand

Accelerate discovery research with DiseaseLand

DiseaseLand is a disease-focused public database containing carefully curated data from multiple data types, including single-cell RNA-seq. Leverage QIAGEN’s world-class informatics pipelines, curation and data management to accelerate your cardiovascular, metabolic, immunologic and neurologic disease projects – from biomarker discovery, new target identification and target validation, to drug repositioning and indication discovery.

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Disease-focused data and analytics

Used in nearly all stages of drug development (from discovery to preclinical and clinical research), DiseaseLand encompasses multi-omics data, while providing a standardized pipeline for incorporation of data, with controlled vocabularies for associated information.

  • Utilize public single-cell RNA-seq data
  • Broad support for genomic data types and thousands of curated and quality-controlled public disease-focused genome datasets
  • Powerful visualization and analytics to compare and correlate within and across datasets
  • Internal “Land” next-generation database technology provides very fast access to a large number of genomic datasets
 

 

Focus on downstream research

No need to reinvent the wheel! QIAGEN’s bioinformatics team spends thousands of computing, curation and download hours each year to keep up with rapidly growing disease-focused genomics data so you don’t have to. By using our pre-curated datasets and powerful analytics, you can:

  • Quickly identify high-quality, well-curated, publicly available disease-focused datasets
  • Find modulation of targets with known compounds and treatments
  • Organize your datasets for compliance with pharma industry data standards
  • Save valuable time and resources, while empowering focused research

Request a trial of DiseaseLand today

 


Capabilities

  • Quality-controlled data from GEO, ArrayExpress, SRA, LINCS, ENA, ImmGen and more
    • Careful metadata curation with controlled vocabulary
    • Reprocessed and normalized expression data
    • Over 1500 clinical measures: Disease, Tissue, Treatment, Survival, Demographics
  • Thousands of recalculated statistical comparisons
  • Microarray, RNA-seq, miRNA, methylation
  • Single-cell RNA-seq: UMI & non-UMI
  • Utilize single-cell RNA-seq to:
    • Discover new biomarkers for transient cell states
    • Identify signatures for rare cell types
    • Compare cell type compositions in disease and normal tissues
 

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