Per-Unit Sequence Models
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
Mechanistic Models: Compartment Models in Individual and Population Analysis
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model
Survival Tree
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
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Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.
Updated: Jan 8, 2026

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
Published on: August 22, 2018
Carlos Martí-Gómez1, David M McCandlish1, Justin B Kinney1
1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, 1 Bungtown Rd., Cold Spring Harbor, 11724, New York, United States.
Los modelos de biología computacional tienen parámetros ambiguos ("libertades de calibre") que dificultan la interpretación. GaugeFixer, un nuevo paquete de Python, resuelve estas ambigüedades con escalado lineal, permitiendo el análisis de grandes paisajes de secuencia-función.
Sus antecedentes:
07:08Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
10:39The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
Published on: May 3, 2018
Conclusiones: