TY - JOUR
T1 - Reconstructing Waddington Landscape from Cell Migration and Proliferation
AU - Han, Yourui
AU - Chen, Bolin
AU - Bi, Zhongwen
AU - Zhang, Jianjun
AU - Hu, Youpeng
AU - Bian, Jun
AU - Kang, Ruiming
AU - Shang, Xuequn
N1 - Publisher Copyright:
© International Association of Scientists in the Interdisciplinary Areas 2025.
PY - 2025
Y1 - 2025
N2 - Abstract: The Waddington landscape was initially proposed to depict cell differentiation, and has been extended to explain phenomena such as reprogramming. The landscape serves as a concrete representation of cellular differentiation potential, yet the precise representation of this potential remains an unsolved problem, posing significant challenges to reconstructing the Waddington landscape. The characterization of cellular differentiation potential relies on transcriptomic signatures of known markers typically. Numerous computational models based on various energy indicators, such as Shannon entropy, have been proposed. While these models can effectively characterize cellular differentiation potential, most of them lack corresponding dynamical interpretations, which are crucial for enhancing our understanding of cell fate transitions. Therefore, from the perspective of cell migration and proliferation, a feasible framework was developed for calculating the dynamically interpretable energy indicator to reconstruct Waddington landscape based on sparse autoencoders and the reaction diffusion advection equation. Within this framework, typical cellular developmental processes, such as hematopoiesis and reprogramming processes, were dynamically simulated and their corresponding Waddington landscapes were reconstructed. Furthermore, dynamic simulation and reconstruction were also conducted for special developmental processes, such as embryogenesis and Epithelial–Mesenchymal Transition process. Ultimately, these diverse cell fate transitions were amalgamated into a unified Waddington landscape.
AB - Abstract: The Waddington landscape was initially proposed to depict cell differentiation, and has been extended to explain phenomena such as reprogramming. The landscape serves as a concrete representation of cellular differentiation potential, yet the precise representation of this potential remains an unsolved problem, posing significant challenges to reconstructing the Waddington landscape. The characterization of cellular differentiation potential relies on transcriptomic signatures of known markers typically. Numerous computational models based on various energy indicators, such as Shannon entropy, have been proposed. While these models can effectively characterize cellular differentiation potential, most of them lack corresponding dynamical interpretations, which are crucial for enhancing our understanding of cell fate transitions. Therefore, from the perspective of cell migration and proliferation, a feasible framework was developed for calculating the dynamically interpretable energy indicator to reconstruct Waddington landscape based on sparse autoencoders and the reaction diffusion advection equation. Within this framework, typical cellular developmental processes, such as hematopoiesis and reprogramming processes, were dynamically simulated and their corresponding Waddington landscapes were reconstructed. Furthermore, dynamic simulation and reconstruction were also conducted for special developmental processes, such as embryogenesis and Epithelial–Mesenchymal Transition process. Ultimately, these diverse cell fate transitions were amalgamated into a unified Waddington landscape.
KW - Cell migration and proliferation
KW - Energy indicator
KW - Reaction diffusion advection equation
KW - Sparse autoencoder
KW - Waddington landscape
UR - http://www.scopus.com/inward/record.url?scp=85214427117&partnerID=8YFLogxK
U2 - 10.1007/s12539-024-00686-z
DO - 10.1007/s12539-024-00686-z
M3 - 文章
AN - SCOPUS:85214427117
SN - 1913-2751
JO - Interdisciplinary Sciences - Computational Life Sciences
JF - Interdisciplinary Sciences - Computational Life Sciences
M1 - e59
ER -