Systems Biology

Inference of drug off-target effects on cellular signaling using interactome-based deep learning

1. Nikolaos Meimetis
2. Douglas A. Lauffenburger
3. Avlant Nilsson

Reviewed by preLights

A unified approach to dissecting biphasic responses in cell signaling

1. Vaidhiswaran Ramesh
2. J Krishnan

• Curated by eLife

  eLife assessment

  This study presents a useful mathematical analysis of different signaling networks in an attempt to provide general rules that give rise to biphasic responses, a widely observed behavior in biology in which the outputs of the network depend non-monotonically on the inputs. Determining general conditions that underlie this behavior would be useful in engineering synthetic biological systems and for mechanistically understanding biphasic responses in biological systems. However, whereas the mathematical approach and methods are solid, as they stand, the analyses are inadequate to assess how these findings are applicable in nature and which are general.

Reviewed by eLife

Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories

1. Jeanette A.I. Johnson
2. Daniel R. Bergman
3. Heber L. Rocha
4. David L. Zhou
5. Eric Cramer
6. Ian C. Mclean
7. Yoseph W. Dance
8. Max Booth
9. Zachary Nicholas
10. Tamara Lopez-Vidal
11. Atul Deshpande
12. Randy Heiland
13. Elmar Bucher
14. Fatemeh Shojaeian
15. Matthew Dunworth
16. André Forjaz
17. Michael Getz
18. Inês Godet
19. Furkan Kurtoglu
20. Melissa Lyman
21. John Metzcar
22. Jacob T. Mitchell
23. Andrew Raddatz
24. Jacobo Solorzano
25. Aneequa Sundus
26. Yafei Wang
27. David G. DeNardo
28. Andrew J. Ewald
29. Daniele M. Gilkes
30. Luciane T. Kagohara
31. Ashley L. Kiemen
32. Elizabeth D. Thompson
33. Denis Wirtz
34. Laura D. Wood
35. Pei-Hsun Wu
36. Neeha Zaidi
37. Lei Zheng
38. Jacquelyn W. Zimmerman
39. Jude M. Phillip
40. Elizabeth M. Jaffee
41. Joe W. Gray
42. Lisa M. Coussens
43. Young Hwan Chang
44. Laura M. Heiser
45. Genevieve L. Stein-O’Brien
46. Elana J. Fertig
47. Paul Macklin

Reviewed by preLights

Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse

1. Zeyneb Kurt
2. Jenny Cheng
3. Rio Barrere-Cain
4. Caden N McQuillen
5. Zara Saleem
6. Neil Hsu
7. Nuoya Jiang
8. Calvin Pan
9. Oscar Franzén
10. Simon Koplev
11. Susanna Wang
12. Johan Björkegren
13. Aldons J Lusis
14. Montgomery Blencowe
15. Xia Yang

• Curated by eLife

  eLife assessment

  In this important study, the authors integrated genetic and genomic datasets from humans and mice to unveil shared networks and pathways associated with coronary artery disease. Their compelling analysis led to the identification of new regulatory genes and pathways in vascular tissues and in the liver, allowing for a more in-depth understanding of the pathogenesis of coronary artery disease.

Reviewed by eLife

The PP2A-like phosphatase Ppg1 mediates assembly of the Far complex to balance gluconeogenic outputs and enables adaptation to glucose depletion

1. Shreyas Niphadkar
2. Lavanya Karinje
3. Sunil Laxman

Reviewed by Review Commons

Quantitative Geometric Modeling of Blood Cells from X-ray Histotomograms of Whole Zebrafish Larvae

1. Maksim A. Yakovlev
2. Ke Liang
3. Carolyn R. Zaino
4. Daniel J. Vanselow
5. Andrew L. Sugarman
6. Alex Y. Lin
7. Patrick J. La Riviere
8. Yuxi Zheng
9. Justin D. Silverman
10. John C. Leichty
11. Sharon X. Huang
12. Keith C. Cheng

• Curated by eLife

  eLife assessment

  Tissue phenotyping is central to nearly all areas of biology. In this study, the authors use an advanced form of micro-CT (X-ray histotomography) in zebrafish to phenotype blood cells in the intact animal. These approaches build upon prior work from this group and others showing this is a scalable imaging method that could readily be applied to other cell types, and provide an excellent complement to histological analysis of tissues. This is important work, as it demonstrates that the method can provide an approach that is orthogonal to conventional histology. The strength of the presented data is compelling, with description of both the hardware and software needed to implement the protocol, which will make it accessible to other researchers in the field.

Reviewed by eLife

Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease

1. Ricardo Omar Ramirez Flores
2. Jan David Lanzer
3. Daniel Dimitrov
4. Britta Velten
5. Julio Saez-Rodriguez

Reviewed by Review Commons

Homeostasis, injury, and recovery dynamics at multiple scales in a self-organizing mouse intestinal crypt

1. Louis Gall
2. Carrie Duckworth
3. Ferran Jardi
4. Lieve Lammens
5. Aimee Parker
6. Ambra Bianco
7. Holly Kimko
8. David Mark Pritchard
9. Carmen Pin

• Curated by eLife

  eLife assessment

  The authors developed a valuable mathematical model that describes the spatiotemporal dynamics of cells in the intestinal crypt. The proposed model makes an important contribution to the field, allowing a better understanding of the formation and response dynamics of the intestinal crypt through the effective evaluation of health, disease, and treatment conditions. The authors provided solid evidence of the validity of their model and their conclusions, but some minor claims are not properly justified in the current manuscript. This paper is meant for computational biologists and cancer researchers working on oncotherapies for the intestinal epithelium.

Reviewed by eLife