慢慢流出
发表于 2025-3-23 09:57:15
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慢跑鞋
发表于 2025-3-23 17:56:03
Alexandre Dolgui,Alain Bernard,David Romeroith separated rate constants can be described by deterministic, acyclic automata with a number of states that is inferior to the number of biochemical species. For nonlinear pathways, we propose a general approach to approximate their dynamics by finite state machines working on the metastable state
Aggressive
发表于 2025-3-23 19:26:28
https://doi.org/10.1007/978-3-030-85906-0obial activity of synthetic and natural peptides where Quantitative Structure-Activity Relationship methodologies are widely used. Traditionally, works focused on designing descriptors for sequences to yield better correlations with the biological activity and improve predictors performance. Albeit
menopause
发表于 2025-3-24 00:51:39
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critic
发表于 2025-3-24 03:06:49
Hyungjoon Yang,Je-Hun Lee,Hyun-Jung Kimtion, comparatively little work has been done on integrated systems that combine all of these aspects. This paper presents an active learning system, “Huginn”, that integrates experiment design and model revision in order to automate scientific reasoning about Metabolic Network Models. We have valid
evince
发表于 2025-3-24 07:47:24
https://doi.org/10.1007/978-3-030-85914-5 nets. The kinetics of reactions need to be described only partially, so that the language can be used to model the regulation of metabolic networks. We present a qualitative reasoning method based on abstract interpretation of the steady state semantics of reaction networks modeled in our language.
真繁荣
发表于 2025-3-24 11:14:46
Hongyuan Luo,Mahjoub Dridi,Olivier Grunderarned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure t
Filibuster
发表于 2025-3-24 17:55:50
Alexandre Dolgui,Alain Bernard,David Romerol that performs . parameter set synthesis for . (ODE) biological models expressed in the . (SBML) given a desired behaviour expressed by time-series data. Three key features of . are: (1) . computes parameter intervals, not just single values; (2) for the identified intervals the model is formally g
灌溉
发表于 2025-3-24 21:55:43
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liposuction
发表于 2025-3-25 02:57:51
https://doi.org/10.1007/978-3-319-23401-4biological networks; computational biology; discrete models; model checking; simulation and modeling; app