找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Computational Modeling of Signaling Networks; Lan K. Nguyen Book 2023 Springer Science+Business Media, LLC, part of Springer Nature 2023 C

[復(fù)制鏈接]
樓主: 粘上
51#
發(fā)表于 2025-3-30 08:31:58 | 只看該作者
A Practical Guide for the Efficient Formulation and Calibration of Large, Energy- and Rule-Based Mod
52#
發(fā)表于 2025-3-30 15:16:06 | 只看該作者
Design Principles Underlying Robust Adaptation of Complex Biochemical Networksosable into just two types of network building-blocks—opposer modules and balancer modules. Here we present an overview of the design principles that characterize all RPA-capable network topologies through a detailed examination of a collection of simple examples. We also introduce a diagrammatic me
53#
發(fā)表于 2025-3-30 16:44:18 | 只看該作者
Multi-Dimensional Analysis of Biochemical Network Dynamics Using pyDYVIPACal to the field of synthetic biology. In this chapter, we will present a practical guide to the multidimensional exploration, analysis, and visualization of network dynamics using pyDYVIPAC, which is a tool ideally suited to these purposes implemented in Python. The utility of pyDYVIPAC will be demo
54#
發(fā)表于 2025-3-30 21:21:46 | 只看該作者
Integrating Multi-Omics Data to Construct Reliable Interconnected Models of Signaling, Gene Regulato regulatory and protein-protein interaction (PPI) links connecting signaling proteins or transcription factors or miRNAs to metabolic enzymes and their metabolites using network analysis and mathematical modeling. These cross-pathway links were shown to play important roles in metabolic reprogrammin
55#
發(fā)表于 2025-3-31 00:52:52 | 只看該作者
Efficient Quantification of Extrinsic Fluctuations via Stochastic Simulations estimate these extrinsic fluctuations for experimentally constructed bidirectional transcriptional reporter systems along with the intrinsic variability. We use the Nanog transcriptional regulatory network and its variants to illustrate our numerical method. Our method reconciled experimental obser
56#
發(fā)表于 2025-3-31 07:03:48 | 只看該作者
Meta-Dynamic Network Modelling for Biochemical Networkseals the range of possible protein dynamics for a given network topology. Since MDN modelling is integrated with traditional ODE modelling, it can also be used to investigate the underlying causal mechanics. This technique is particularly suited to the investigation of network behaviors in systems t
57#
發(fā)表于 2025-3-31 10:55:48 | 只看該作者
58#
發(fā)表于 2025-3-31 14:52:26 | 只看該作者
59#
發(fā)表于 2025-3-31 18:04:44 | 只看該作者
Resolving Crosstalk Between Signaling Pathways Using Mathematical Modeling and Time-Resolved Single of p53 to genotoxic stress using time-resolved single cell data and perturbed NF-κB signaling by inhibiting the kinase IKK2. Employing a subpopulation-based modeling approach enabled us to identify multiple interaction points that are simultaneously affected by perturbation of NF-κB signaling. Henc
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-17 03:06
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
乃东县| 奇台县| 财经| 噶尔县| 宜章县| 黑河市| 平和县| 和静县| 河津市| 琼海市| 高唐县| 广灵县| 马关县| 三门县| 嘉义县| 阳原县| 闵行区| 土默特左旗| 莱州市| 武宁县| 楚雄市| 寻乌县| 涿鹿县| 十堰市| 苍梧县| 定日县| 赤水市| 五台县| 嘉禾县| 宁晋县| 石景山区| 蒙自县| 安义县| 界首市| 公主岭市| 玉溪市| 西乡县| 淳安县| 云龙县| 深水埗区| 荆州市|