CellBox: interpretable machine learning for perturbation biology with application to the design of cancer combination therapy
Systematic perturbation of cells followed by comprehensive measurements of molecular and
phenotypic responses provides informative data resources for constructing computational …
phenotypic responses provides informative data resources for constructing computational …
Deep learning of causal structures in high dimensions under data limitations
K Lagemann, C Lagemann, B Taschler… - Nature Machine …, 2023 - nature.com
Causal learning is a key challenge in scientific artificial intelligence as it allows researchers
to go beyond purely correlative or predictive analyses towards learning underlying cause …
to go beyond purely correlative or predictive analyses towards learning underlying cause …
Inferring causal molecular networks: empirical assessment through a community-based effort
It remains unclear whether causal, rather than merely correlational, relationships in
molecular networks can be inferred in complex biological settings. Here we describe the …
molecular networks can be inferred in complex biological settings. Here we describe the …
Resource allocation in mammalian systems
HM Baghdassarian, NE Lewis - Biotechnology Advances, 2024 - Elsevier
Cells execute biological functions to support phenotypes such as growth, migration, and
secretion. Complementarily, each function of a cell has resource costs that constrain …
secretion. Complementarily, each function of a cell has resource costs that constrain …
Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data
BM Invergo, P Beltrao - Essays in Biochemistry, 2018 - portlandpress.com
Cascades of phosphorylation between protein kinases comprise a core mechanism in the
integration and propagation of intracellular signals. Although we have accumulated a wealth …
integration and propagation of intracellular signals. Although we have accumulated a wealth …
Patient‐specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies
Mechanistic modeling of signaling pathways mediating patient‐specific response to therapy
can help to unveil resistance mechanisms and improve therapeutic strategies. Yet, creating …
can help to unveil resistance mechanisms and improve therapeutic strategies. Yet, creating …
Drug resistance mechanisms in colorectal cancer dissected with cell type–specific dynamic logic models
Genomic features are used as biomarkers of sensitivity to kinase inhibitors used widely to
treat human cancer, but effective patient stratification based on these principles remains …
treat human cancer, but effective patient stratification based on these principles remains …
[HTML][HTML] Establishing institutional scores with the rigor and transparency index: large-scale analysis of scientific reporting quality
Background Improving rigor and transparency measures should lead to improvements in
reproducibility across the scientific literature; however, the assessment of measures of …
reproducibility across the scientific literature; however, the assessment of measures of …
Causal interactions from proteomic profiles: Molecular data meet pathway knowledge
We present a computational method to infer causal mechanisms in cell biology by analyzing
changes in high-throughput proteomic profiles on the background of prior knowledge …
changes in high-throughput proteomic profiles on the background of prior knowledge …
Computational discovery of dynamic cell line specific Boolean networks from multiplex time-course data
Protein signaling networks are static views of dynamic processes where proteins go through
many biochemical modifications such as ubiquitination and phosphorylation to propagate …
many biochemical modifications such as ubiquitination and phosphorylation to propagate …