Evidence map›Paper›PMID 42071138›Full record

ReviewAdvances in experimental medicine and biology2026

Microarrays and the Dawn of Omics Data Analysis.

Margarida Gama-Carvalho, Lisete Sousa

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Margarida Gama-CarvalhoFaculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal. mhcarvalho@fc.ul.pt.ORCID https://orcid.org/0000-0002-0365-6916
Lisete SousaFaculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microarrays have played a pivotal role in the early stages of omics data generation and analysis. For over 15 years, microarray technology dominated the field of transcriptomics, providing high-throughput platforms to measure gene expression levels across thousands of genes simultaneously. Microarrays enabled a wide range of genomic studies, leading to a vast repository of data in public databases such as the Gene Expression Omnibus (GEO). However, with the advent of next-generation sequencing (NGS), the use of microarrays has steadily declined. Despite this, the legacy of microarrays persists, particularly through the wealth of data generated over the years, which continues to fuel genomic research today. This chapter reviews the origins of microarrays and their impact on omics research and discusses the basic principles behind the technology, how it has evolved over the years, and how it lay the groundwork for the field as we know it today.

Indexed as

Gene Expression ProfilingGenomicsOligonucleotide Array Sequence AnalysisAnimalsDatabases, GeneticHigh-Throughput Nucleotide SequencingHumansMultiomicsTranscriptomeData analysisDNA chipsGenomicsMicroarraysOligonucleotide arraysTranscriptomics

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.