Systems Biology

The ability to sense the environment is heterogeneously distributed in cell populations

1. Andrew Goetz
2. Hoda Akl
3. Purushottam Dixit

• Curated by eLife

  eLife assessment

  In this valuable paper, the authors use an existing theoretical framework relying on information theory and maximum entropy inference in order to quantify how much information single cells can carry, taking into account their internal state. They reanalyze experimental data in this light. Despite some limitations of the data, the study convincingly highlights the difference between single-cell and population channel capacities. This result should be of interest to the quantitative biology community, as it contributes to explaining why channel capacities are apparently low in cells.

Reviewed by eLife

Knock-down of a regulatory barcode shifts macrophage polarization destination from M1 to M2 and increases pathogen burden upon S. aureus infection

1. Sathyabaarathi Ravichandran
2. Bharat Bhatt
3. Awantika Shah
4. Kithiganahalli Narayanaswamy Balaji
5. Nagasuma Chandra

• Curated by eLife

  eLife assessment

  The authors of this manuscript address the following question in the immunology field: what are the transcriptional regulators that allow macrophages to assume different functional phenotypes in response to immune stimuli? They generate a computational map of the gene regulatory networks involved in determining macrophage phenotypes and experimentally validate the role of putative regulatory factors in a myeloid cell line. This study represents a valuable approach to understanding how gene regulation impacts macrophage polarization but the analyses remain incomplete without further validation in primary cells or by examining the identified genes in the in vivo setting.

Reviewed by eLife

Liebig’s law of the minimum in the TGF-β/SMAD pathway

1. Yuchao Li
2. Difan Deng
3. Chris Tina Höfer
4. Jihye Kim
5. Won Do Heo
6. Quanbin Xu
7. Xuedong Liu
8. Zhike Zi

Reviewed by Review Commons

Dynamic analysis and control of a rice-pest system under transcritical bifurcations

1. Sajib Mandal
2. Sebastian Oberst
3. Md. Haider Ali Biswas
4. Md. Sirajul Islam

Reviewed by PeerJ

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

Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications

1. Rafael F Guerrero
2. Tandin Dorji
3. Ra'Mal M Harris
4. Matthew D Shoulders
5. C Brandon Ogbunugafor

• Curated by eLife

  eLife assessment

  This manuscript introduces two valuable new metrics - "variant vulnerability" and "drug applicability" - that would be of use to identify candidate drugs for treating infections while considering longer-term, evolution-based treatment outcomes. Despite the intuitive appeal of the metrics and their potential, the study remains incomplete, as it fails to demonstrate the generality of the approach. The work could be improved by analysing a broader range of data in a systematic way and directly tying the metrics to outcomes, which would make it possible to better assess their impact and utility.

Reviewed by eLife

Evaluating Study Design Rigor in Preclinical Cardiovascular Research: A Replication Study

1. Isaiah C. Jimenez
2. Gabrielle C. Montenegro
3. Keyana Zahiri
4. Damini Patel
5. Adrienne Mueller

• Curated by eLife

  eLife assessment

  The article has important scientific merit in the field of cardiovascular research and other fields where the design and rigor of scientific experiments is key for translation of preclinical research to clinical studies. This study holds convincing evidence that sheds light on the lack of progress in this area over the past decade, despite a substantial body of existing research. Although there is a need to re-evaluate the statistical test used, the descriptive paper outcomes serves as a compelling call to action for the wider scientific community.

Reviewed by eLife

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

Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

1. Jeanette A.I. Johnson
2. Genevieve L. Stein-O’Brien
3. Max Booth
4. Randy Heiland
5. Furkan Kurtoglu
6. Daniel R. Bergman
7. Elmar Bucher
8. Atul Deshpande
9. André Forjaz
10. Michael Getz
11. Ines Godet
12. Melissa Lyman
13. John Metzcar
14. Jacob Mitchell
15. Andrew Raddatz
16. Heber Rocha
17. Jacobo Solorzano
18. Aneequa Sundus
19. Yafei Wang
20. Danielle Gilkes
21. Luciane T. Kagohara
22. Ashley L. Kiemen
23. Elizabeth D. Thompson
24. Denis Wirtz
25. Pei-Hsun Wu
26. Neeha Zaidi
27. Lei Zheng
28. Jacquelyn W. Zimmerman
29. Elizabeth M. Jaffee
30. Young Hwan Chang
31. Lisa M. Coussens
32. Joe W. Gray
33. Laura M. Heiser
34. Elana J. Fertig
35. 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