Eleven grand challenges in single-cell data science
Abstrak
The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands—or even millions—of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
Penulis (51)
David Lähnemann
Johannes Köster
Ewa Szczurek
Davis J. McCarthy
S. Hicks
M. Robinson
C. Vallejos
Kieran R. Campbell
N. Beerenwinkel
A. Mahfouz
Luca Pinello
P. Skums
A. Stamatakis
Camille Stephan-Otto Attolini
Samuel Aparicio
J. Baaijens
M. Balvert
B. D. Barbanson
A. Cappuccio
G. Corleone
B. Dutilh
M. Florescu
V. Guryev
Rens Holmer
Katharina Jahn
T. J. Lobo
Emma M. Keizer
Indu Khatri
S. Kiełbasa
J. Korbel
Alexey M. Kozlov
Tzu-Hao Kuo
B. Lelieveldt
I. Măndoiu
J. Marioni
T. Marschall
Felix Mölder
A. Niknejad
Lukasz Raczkowski
M. Reinders
J. Ridder
A. Saliba
A. Somarakis
O. Stegle
Fabian J Theis
Huan Yang
A. Zelikovsky
A. Mchardy
Benjamin J. Raphael
Sohrab P. Shah
A. Schönhuth
Akses Cepat
- Tahun Terbit
- 2020
- Bahasa
- en
- Total Sitasi
- 1120×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1186/s13059-020-1926-6
- Akses
- Open Access ✓