Computational and Systems Biology

eLife assessment

This valuable manuscript presents ImmCellTyper, a new toolkit for CyTOF data analysis. The semi-supervised clustering tool, BinaryClust, integrates prior biological knowledge and demonstrates competitive performance in various benchmarks, but there is room for strengthening the evidence base by addressing concerns about incomplete benchmarking results and the limited consideration of CyTOF markers with binary distribution. Overall, the manuscript offers solid potential for enhancing CyTOF data analysis methodologies.

eLife assessment

This study presents an important computational tool for the quantification of the cellular composition of human tissues profiled with ATAC-seq. The methodology is solid and its application results on breast cancer tumor tissues are convincing. It advances existing methods by utilizing a comprehensive reference profile for major cancer-relevant cell types, compatible with a widely-used cell type deconvolution tool.

eLife assessment

In this important study, the authors manually assessed randomly selected images published in eLife between 2012 and 2020 to determine whether they were accessible for readers with deuteranopia, the most common form of color vision deficiency. They then developed an automated tool designed to classify figures and images as either "friendly" or "unfriendly" for people with deuteranopia. While such a tool could be used by publishers, editors or researchers to monitor accessibility in the research literature, the evidence supporting the tools' utility was incomplete. The tool would benefit from training on an expanded dataset that includes different image and figure types from many journals, and using more rigorous approaches when training the tool and assessing performance. The authors also provide code that readers can download and run to test their own images. This may be of most use for testing the tool, as there are already several free, user-friendly recoloring programs that allow users to see how images would look to a person with different forms of color vision deficiency. Automated classifications are of most use for assessing many images, when the user does not have the time or resources to assess each image individually.

eLife assessment

This study presents a useful examination of the prevalence of interactions between amino acids from different periods of Earth's history and coenzymes. While the premise of this work is compelling, the data lend themselves to alternative interpretations, suggesting that the main conclusions might not be entirely supported by the findings. The work would benefit from the inclusion of additional supplementary data and further analysis. This manuscript would be of interest to evolutionary biologists and biophysicists.

eLife assessment

Pluripotent stem cells can be obtained from embryos (embryonic stem cells, ESCs) or through induction by transfection (induced pluripotent stem cells, iPSCs). This valuable study uses semi-quantitative proteomics to compare both types of cells, finding interesting differences. The value of the study lies in demonstrating that ESCs and iPSCs cannot be used interchangeably. The conclusions are backed by solid data even if a greater number and diversity in ESC and iPSC clones would help in generalizing the observations.

eLife assessment

This landmark study presents MetaPathPredict, a method that uses a stacked ensemble of neural networks to predict the presence or absence of KEGG modules based on annotated features in the genome. The evidence supporting the conclusions is compelling, with a tool that allows for prediction of KEGG modules in sparse gene sequence datasets.

eLife assessment

By taking advantage of noise in gene expression, this important study introduces a new approach for detecting directed causal interactions between two genes without perturbing either. The main theoretical result is supported by a proof, although clearer statements are needed to ensure that there are no edge cases that can violate the theorem. Preliminary simulations and experiments on small circuits are presented, but the evidence remains incomplete because further investigations are needed to demonstrate the broad applicability and scalability of the method.

eLife assessment

This study presents a cellular automaton model to study the dynamics of virus-induced signalling and innate host defense against viruses such as SARS-CoV-2 in epithelial tissue. The data presented are convincing and represent a valuable contribution that would be of interest to researchers studying the dynamics of viral propogation. The significance of the study might be further elevated with more details on the reduction of expression data to the model rules discussed.

eLife assessment

The authors introduce a valuable machine-learning model for predicting binding sites of diverse ligands, including DNA, RNA, peptides, proteins, ATP, HEM, and metal ions, on proteins. The method is freely accessible and user-friendly. The authors have conducted thorough benchmarking and ablation studies, providing convincing evidence of the model's overall performance, despite some imperfections of the comparisons to other methods that arise from intrinsic differences between training methods and data.

eLife assessment

This so-far most comprehensive, spatially resolved in 2D, dynamical, multicellular model of murine muscle regeneration after injury is is an attempt to combine many contributors to muscle regeneration into one coherent calibrated framework. It has the potential to be a very valuable tool in the areas of tissue morphogenesis, regenerative therapies, quantitative modeling and simulation. However, the presentation of the experimental validation is incomplete.

eLife assessment

This study presents a valuable model for the emergence of planar cell polarity from the interplay of local interactions and global gradient. The framework of this model is solid, although the appreciation of its result should in places be more quantitative. A quality of this model is its simplicity and its convenience for experimental testing.

eLife assessment

In this important manuscript, the authors used unbiased approaches to identify somatic mutations in publicly available databases that would disrupt clinically approved antibodies targeting HER2. Using a solid combination of both computational and experimental approaches they identify mutations that could restore therapeutic antibody sensitivity in a series of disease-relevant model systems. Additional cell-based and in vivo assays would strengthen the work and increase the translational and potential clinical relevance of the proposed work.

eLife assessment

This study presents an advance in efforts to use histone post-translational modification (PTM) data to model gene expression and predict epigenetic editing activity. Such models are broadly useful to the research community, especially ones that can model epigenetic editing activity, which is novel. However, whereas the authors have nicely integrated datasets across cell types into their model, the work is incomplete in two key areas: (1) a lack of comparisons to existing models that predict gene expression from PTM data makes it unclear what advantages the current model offers, and (2) more rigorous experimental evidence for dCas9-based perturbations is needed to rigorously assess how well the model predicts epigenetic editing outcomes.

eLife assessment

This study presents a useful tool for predicting TCR specificity with compelling evidence for improvements over prior art. This work/tool will be broadly relevant to computational biologists and immunologists.

eLife assessment

This study presents a useful deep learning-based inter-protein contact prediction method named PLMGraph-Inter which combines protein language models and geometric graphs. The evidence supporting the claims of the authors is solid. The authors show that their approach may be used in cases where AlphaFold-Multimer performs poorly. This work will be of interest to researchers working on protein complex structure prediction, particularly when accurate experimental structures are available for one or both of the monomers in isolation.

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.

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.

eLife assessment

This valuable study advances our understanding of the relationship between different mammalian ligands and receptors of the Notch signaling pathway. The authors systematically evaluate the effects of different combinations of ligands and receptors on levels of pathway activation. The convincing though not always complete data uncover interesting and unexpected differences, which provide a foundation for interpreting Notch signaling events in normal and disease contexts where this pathway operates.

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.

eLife assessment

This useful manuscript explores conditions for epigenetic inheritance by studying the stability of simple network models to permanent and transient perturbations. A novel aspect of the study is that it unifies non-genetic inheritance phenomena across cell divisions of unicellular organisms and in the germline of multicellular organisms. However, the models studied are more a collection of vignettes of numerical studies than a systematic study, therefore the evidence presented remains incomplete. As a first step towards building a more systematic theoretical framework, this work will be of interest to colleagues in the field of epigenetic inheritance.