Single cell <scp>RNA</scp> seq of the major cell types in the larva of the sea star, <i>Patiria miniata</i>

This dataset from the sea star provides a developmental trajectory of gene expression leading to each major cell type in the larva, providing a foundation for comparative analysis with other echinoderm species in parsing out mechanisms of developmental specification, regeneration, and germ line formation.

Authors

Institutions

Publication Details

Journal
Developmental Dynamics
Published
2025-11-27
DOI
https://doi.org/10.1002/dvdy.70100
Primary Topic
Echinoderm biology and ecology
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Single cell RNA seq of the major cell types in the larva of the sea star, Patiria miniata

Gary M. Wessel, Stephany Foster, Nathalie Oulhen, Gerardo Reyes
Developmental Dynamics
Echinoderm biology and ecology
article

Single cell RNA seq of the major cell types in the larva of the sea star, Patiria miniata

Gary M. Wessel, Stephany Foster, Nathalie Oulhen, Gerardo Reyes
article en

Abstract

This dataset from the sea star provides a developmental trajectory of gene expression leading to each major cell type in the larva, providing a foundation for comparative analysis with other echinoderm species in parsing out mechanisms of developmental specification, regeneration, and germ line formation.

Developmental Dynamics
Brown University (US)
National Science Foundation, National Institutes of Health
Openalex Percentile: Top 67%
Echinoderm biology and ecology
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.