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Every paper Pith has read. Search by title, abstract, or pith.
24 papers in q-bio.MN · page 1
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Methylation feedback dynamically reshapes gene expression
Autonomous Reshaping of Expression Landscapes by DNA Methylation
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Vertex measures match VR in spotting cancer genes
Scalable vertex guided filtrations identify structurally relevant genes in cancer networks
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One futile cycle network combines bistability with fixed final product
Bistability, Absolute Concentration Robustness, and Hysteresis in Dual-Site Futile Cycles with Bifunctional Enzymes
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Bursting gene networks reach unique equilibria with explicit rates
Quantitative ergodicity for gene regulatory networks with transcriptional bursting
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Switching control makes gene densities forget their initial state
Predictive-Switching Control of Stochastic Gene Regulatory Networks: A Contractive PIDE Framework
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MaxSMT infers qualitative models up to 1300 genes from noisy data
Inference of Qualitative Models from Steady-State Data via Weighted MaxSMT
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Weighted MaxSMT finds biological models despite conflicting observations
Inference of Qualitative Models from Steady-State Data via Weighted MaxSMT
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Burst timing shapes vesicle signaling activation
Activation in Vesicle-Mediated Signaling Shaped by Batch Arrival Statistics
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Ocean microbe networks exceed null modularity by 0.15-0.40
Modularity Emerges from Action-Functional Constraints in Marine Metabolic Networks: A Biology-Scale Validation of the Network-Weighted Action Principle
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Logarithmic method recovers adiabatic scaling in excitable systems
Breakdown of Adiabatic Scaling and Noise-Induced Functional Synchronization in Deeply Quiescent Excitable Systems
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Log centroid recovers Kramers scaling until noise boundary in excitable cells
Breakdown of Adiabatic Scaling and Noise-Induced Functional Synchronization in Deeply Quiescent Excitable Systems
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Logistic functions fix three flaws of Hill models in gene networks
Logistic Gene Regulatory Networks: Prevention of Expression Shutdown, and Numerical Stability Beyond Hill Function
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Pruning protocol shrinks osteogenesis network models to six viable ones
Parsimonious computational inference protocol for Boolean networks: Application to osteogenesis
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Bayesian method infers nucleic acid motif rates from ligation data
Bayesian Rate Inference for Sequence Motif Dynamics in Systems of Reactive Nucleic Acids
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Biophysical consistency separates true gene models from data fits
Learning biophysical models of gene regulation with probability flow matching
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Frozen confidence scores boost multi-omics cancer subtyping
CMGL: Confidence-guided Multi-omics Graph Learning for Cancer Subtype Classification
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Noise switches frustrated genes to set cell differentiation timing
Noise-Driven Differentiation via Gene Frustration and Epigenetic Fixation
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Bacterial growth curves classify nonlinear patterns as reservoirs
What Makes a Bacterial Model a Good Reservoir Computer? Predicting Performance from Separability and Similarity
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Rescaling absorbs kinetic noise to stabilize biochemical waves
Mathematical modeling of biochemical signal propagation in many-stage enzymatic pathways
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Four or more distinct rows block non-vacuous ACR in zero-one networks
Absolute Concentration Robustness of Non-Redundant Zero-One Networks with Conservation Laws
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Propagation computes exact Shapley values for acyclic gene networks
Efficient Shapley values computation for Boolean network models of gene regulation
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Gradient task analysis requires 40% sample overlap to be reliable
Information-Theoretic Requirements for Gradient-Based Task Affinity Estimation in Multi-Task Learning
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AND-gate wiring diagrams fix the exact number of stable states
A modular approach to achieve multistationarity using AND-gates
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Context conditioning enables accurate predictions on targets with only 67 examples
When Does Context Help? A Systematic Study of Target-Conditional Molecular Property Prediction
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Background subtraction rescues TF signatures for 59 of 61 factors
Re-analysis of the Human Transcription Factor Atlas Recovers TF-Specific Signatures from Pooled Single-Cell Screens with Missing Controls
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Dynamic graphs frame multicellular gene control from general principles
Control of genes by self-organizing multicellular interaction networks