Systems Biology

CompoundRay, an open-source tool for high-speed and high-fidelity rendering of compound eyes

1. Blayze Millward
2. Steve Maddock
3. Michael Mangan

• Curated by eLife

  Evaluation Summary:

  This work reports on a mathematical modeling system and associated software implementation for compound eye vision. A critical advance reported here is the ability to model each ommatidium with independent properties and on a software implementation that runs in real time, with tantalizing applications in both modeling biological systems such as insect compound eyes, and the exploration of the possible applications of compound eye vision in robotics.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their name with the authors.)

Reviewed by eLife

Patient-specific Boolean models of signalling networks guide personalised treatments

1. Arnau Montagud
2. Jonas Béal
3. Luis Tobalina
4. Pauline Traynard
5. Vigneshwari Subramanian
6. Bence Szalai
7. Róbert Alföldi
8. László Puskás
9. Alfonso Valencia
10. Emmanuel Barillot
11. Julio Saez-Rodriguez
12. Laurence Calzone

• Curated by eLife

  Evaluation Summary:

  This paper presents a mathematical model for prioritizing drugs for prostate cancer patients based on signal network database. The manuscript is of broad interest to the field of oncology and precision medicine. The methodology developed is sophisticated and relevant to real patient prostate cancer data. The predictions from the model are validated in an experimental setting and provide suggestions for the personalisation of prostate cancer treatment. The study can serve as a roadmap for future development of predictive, personalized models.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

Reviewed by eLife

A qualitative mathematical model of immunocompetence with applications to SARS-CoV-2 immunity

1. Javier Burgos-Salcedo

Reviewed by ScreenIT

PEPPI: Whole-proteome Protein-protein Interaction Prediction through Structure and Sequence Similarity, Functional Association, and Machine Learning

1. Eric W. Bell
2. Jacob H. Schwartz
3. Peter L. Freddolino
4. Yang Zhang

Reviewed by ScreenIT

Defining hierarchical protein interaction networks from spectral analysis of bacterial proteomes

1. Mark A Zaydman
2. Alexander S Little
3. Fidel Haro
4. Valeryia Aksianiuk
5. William J Buchser
6. Aaron DiAntonio
7. Jeffrey I Gordon
8. Jeffrey Milbrandt
9. Arjun S Raman

• Curated by eLife

  Evaluation Summary:

  Since the inception of comparative genomics, mining phyletic patterns has been a powerful approach for the discovery of previously unknown biological interactions. The authors use a combination of singular value decomposition of the phyletic pattern matrix and random forests classification method to uncover potential protein-protein interactions. The work illustrates the utility of such methods, which are finding increasing application in addressing various computational biological problems, such as predicting protein-protein interactions from genomic information.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

Reviewed by eLife

An interactome landscape of SARS-CoV-2 virus-human protein-protein interactions by protein sequence-based multi-label classifiers

1. Ho-Joon Lee

Reviewed by ScreenIT

Multisensory-motor integration in olfactory navigation of silkmoth, Bombyx mori, using virtual reality system

1. Mayu Yamada
2. Hirono Ohashi
3. Koh Hosoda
4. Daisuke Kurabayashi
5. Shunsuke Shigaki

• Curated by eLife

  Evaluation Summary:

  This paper uses a multi-model virtual reality system to assess which combinations of visual, wind, and olfactory information male silk moths rely on to find a female. The overall conclusion is that for the moths to search effectively, wind direction information is an important input. Vision, on the other hand, while it is used to control angular velocity, does not appear to be important for the moths to search effectively. This paper is of interest to neuroscientists and engineers interested in how multimodal sensory input controls navigational behavior. The experiments and modeling effort provide an advance in our understanding of how odor and wind information are combined in male silkmoths as they search for females.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

Reviewed by eLife

High-resolution mapping of the period landscape reveals polymorphism in cell cycle frequency tuning

1. Zhengda Li
2. Shiyuan Wang
3. Meng Sun
4. Minjun Jin
5. Daniel Khain
6. Qiong Yang

• Curated by eLife

  Evaluation Summary:

  This paper uses microfluidics and Xenopus extracts to investigate the effects of mitotic feedbacks on the cell cycle period. It is shown that the inhibition of G2 regulatory positive feedback loops does not reduce the tunability of the cell cycle oscillations, while interference with PP2A phosphatase can completely block of the cell cycle. The experiments are well-conducted and the results should be of interest to researchers interested in the cell cycle, specifically in the regulation of mitosis.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

Reviewed by eLife

A unified framework for measuring selection on cellular lineages and traits

1. Shunpei Yamauchi
2. Takashi Nozoe
3. Reiko Okura
4. Edo Kussell
5. Yuichi Wakamoto

• Curated by eLife

  Evaluation Summary:

  The manuscript by Wakamoto and colleagues presents a general statistical framework to infer selection on a quantitative trait based on measurements of the values of this trait along related cell lineages. The manuscript provides both a detailed explanation of the mathematical underpinnings of the method and an illustration of its application to existing and new cell lineage datasets. The framework is widely applicable to general exponentially growing populations and is not tailored to particular growth models or environmental conditions.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #3 agreed to share their name with the authors.)

Reviewed by eLife

Mutational Signatures as Sensors of Environmental Exposures: Role of Smoking in COVID-19 Vulnerabilities

1. Yoo-Ah Kim
2. Ermin Hodzic
3. Ariella Saslafsky
4. Damian Wojtowicz
5. Bayarbaatar Amgalan
6. Teresa M. Przytycka

Reviewed by ScreenIT