作者: magnate 時(shí)間: 2025-3-21 22:02 作者: Tailor 時(shí)間: 2025-3-22 03:22
Sustainable Tertiary Education in Asialusters of densely connected cells. This subpopulation structure represents a map of putative cell-state transitions. CellRouter implements a flow network algorithm to explore this map and reconstruct cell-state transitions in complex single-cell, multidimensional omics datasets. We describe a step-作者: certain 時(shí)間: 2025-3-22 06:44
André Matthes,Katja Beyer,Anton Schumannl biologists. We focus specifically on the use of one tool, called Iterative Clustering and Guide-gene Selection (ICGS), which has been shown to uncover novel committed, transitional, and metastable progenitor cell states. As a component of the AltAnalyze toolkit, ICGS provides advanced methods to e作者: 有毛就脫毛 時(shí)間: 2025-3-22 10:26
Modeling Cellular Differentiation and Reprogramming with Gene Regulatory Networks GRN can enable control of the eventual cell fates with potential clinical applications. In this chapter, we describe our computational methodologies that we have tailor-made with purpose of applications to cell fate control. Briefly, we introduce the process of cellular differentiation and reprogra作者: 規(guī)章 時(shí)間: 2025-3-22 15:47
Computational Tools for Quantifying Concordance in Single-Cell Fateifetime and to model the deterministic effect of cell environment and inheritance, i.e., nature versus nurture. We have applied competing risks statistics, a branch of survival statistics, to quantify cell fate concordance from cell lifetime data. Competing risks modelling of cell fate concordance p作者: 規(guī)章 時(shí)間: 2025-3-22 19:12 作者: 碎石頭 時(shí)間: 2025-3-23 00:53
Investigating Cell Fate Decisions with ICGS Analysis of Single Cellsl biologists. We focus specifically on the use of one tool, called Iterative Clustering and Guide-gene Selection (ICGS), which has been shown to uncover novel committed, transitional, and metastable progenitor cell states. As a component of the AltAnalyze toolkit, ICGS provides advanced methods to e作者: 法官 時(shí)間: 2025-3-23 02:13 作者: 背心 時(shí)間: 2025-3-23 08:56
https://doi.org/10.1007/978-1-4939-9224-9gene regulatory networks; single-cell transcriptome data; teratomas; engineered cells; fetal tissues作者: 音的強(qiáng)弱 時(shí)間: 2025-3-23 10:34 作者: Lineage 時(shí)間: 2025-3-23 15:53 作者: Insufficient 時(shí)間: 2025-3-23 19:31
Methods in Molecular Biologyhttp://image.papertrans.cn/c/image/233147.jpg作者: champaign 時(shí)間: 2025-3-23 22:21
Computational Stem Cell Biology978-1-4939-9224-9Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: larder 時(shí)間: 2025-3-24 04:05
https://doi.org/10.1007/978-981-10-5062-6nization. However, these models have been previously inaccessible to many systems biologists due to the difficulties with formulating and simulating multi-scale behavior. In this chapter, a review of the Compucell3D framework is presented along with a general workflow for transitioning from a well-m作者: 共同生活 時(shí)間: 2025-3-24 08:23
https://doi.org/10.1007/978-981-19-4847-3o coordinate and maintain the overall gene expression profile observed in a cell is a key question in cellular biology. However, the immense complexity arising due to the scale and the nature of gene-gene interactions often hinders obtaining a global understanding of gene regulation. In this regard,作者: 真實(shí)的你 時(shí)間: 2025-3-24 14:35
https://doi.org/10.1007/978-981-19-4847-3bryonic stem cells or induced pluripotent stem cells can be achieved by exposing them to a succession of signaling conditions meant to mimic developmental milieus. However, achieving a quantitative understanding of the relationship between proliferation, cell death, and commitment has been difficult作者: 充滿人 時(shí)間: 2025-3-24 18:00 作者: 吹牛大王 時(shí)間: 2025-3-24 21:03
https://doi.org/10.1007/978-981-19-4847-3ly multicellular data of cell clones can be obtained. In this situation, experimental data?alone is not sufficient to validate biological models because the hypotheses and the data?cannot be directly compared and thus standard statistical tests cannot be leveraged. On the other hand, mathematical mo作者: Overstate 時(shí)間: 2025-3-25 00:30
Avinash S. Welankiwar,Sagar Kudkelwaractors control cell fate is fundamental to many biological experiments. However, due to transcriptional heterogeneity or microenvironmental fluctuations, cell fates appear to be random. Individual cells within well-defined subpopulations vary with respect to their proliferative potential, survival, 作者: 全面 時(shí)間: 2025-3-25 04:43 作者: Climate 時(shí)間: 2025-3-25 09:19
Sustainable Tertiary Education in Asia profiles. Understanding this multistable behavior is key to rationally influencing stem cell differentiation for both research and therapeutic purposes. To this end, mathematical paradigms have been adopted to simulate and explain the dynamics of complex gene networks. In this chapter, we introduce作者: 乞丐 時(shí)間: 2025-3-25 13:38 作者: 削減 時(shí)間: 2025-3-25 19:42
Stephanie W. Lee,Samson C. W. Ma,Ngok Leetranscriptional state that occur as cells progress through development and adopt specialized cell fates. In this chapter we describe in detail how to use our network inference algorithm (PIDC)—and the associated software package NetworkInference.jl—to infer functional interactions between genes from作者: Absenteeism 時(shí)間: 2025-3-25 23:19 作者: 滲透 時(shí)間: 2025-3-26 03:00
André Matthes,Katja Beyer,Anton Schumannrn lineage commitment. Such cell states include multipotent progenitors that can manifest as mixed-lineage patterns of gene expression at a single-cell level. Multipotent and other self-renewing progenitors are often difficult to isolate and characterized by subtle transcriptional differences that a作者: 消散 時(shí)間: 2025-3-26 07:28
Cem Ba??ran,Ay?egül K?rlü,Saadet Yaparstanding questions in biology with an unprecedented resolution. Among the various applications of scRNA-seq, (1) discovery of novel rare cell types, (2) characterization of heterogeneity among the seemingly homogenous population of cells described by cell surface markers, (3) stem cell identificatio作者: 槍支 時(shí)間: 2025-3-26 11:30 作者: amphibian 時(shí)間: 2025-3-26 16:19 作者: antidote 時(shí)間: 2025-3-26 18:00 作者: deciduous 時(shí)間: 2025-3-26 21:08 作者: FAWN 時(shí)間: 2025-3-27 01:24 作者: 行乞 時(shí)間: 2025-3-27 08:33
https://doi.org/10.1007/978-981-19-4847-3via analytical calculation or stochastic simulations of the model’s Master equation, and to predict the outcomes of clonal statistics for respective hypotheses. We also illustrate two approaches to compare these predictions directly with the clonal data to assess the models.作者: 序曲 時(shí)間: 2025-3-27 09:56
Sustainable Tertiary Education in Asia landscape. Hopfield networks are auto-associative artificial neural networks; input patterns are stored as attractors of the network and can be recalled from noisy or incomplete inputs. The resulting models capture the temporal dynamics of a gene regulatory network, yielding quantitative insight into cellular development and phenotype.作者: landmark 時(shí)間: 2025-3-27 15:44 作者: 套索 時(shí)間: 2025-3-27 20:32 作者: endure 時(shí)間: 2025-3-27 23:38
Cem Ba??ran,Ay?egül K?rlü,Saadet Yaparmajor interest. Therefore, here we present an in-house state-of-the-art scRNA-seq data analyses workflow for de novo lineage tree inference and stem cell identity prediction applicable to many biological processes under current investigation.作者: 某人 時(shí)間: 2025-3-28 03:42
Cem Ba??ran,Ay?egül K?rlü,Saadet Yaparcol outlines the steps for modeling steady-state and dynamic metabolic behavior using transcriptomics and time-course metabolomics data, respectively. Using data from naive and primed pluripotent stem cells, we demonstrate how we can use genome-scale modeling and DFA to comprehensively characterize the metabolic differences between these states.作者: Malleable 時(shí)間: 2025-3-28 06:33 作者: 安慰 時(shí)間: 2025-3-28 13:55
Quantitative Modelling of the Waddington Epigenetic Landscape landscape. Hopfield networks are auto-associative artificial neural networks; input patterns are stored as attractors of the network and can be recalled from noisy or incomplete inputs. The resulting models capture the temporal dynamics of a gene regulatory network, yielding quantitative insight into cellular development and phenotype.作者: 龍蝦 時(shí)間: 2025-3-28 16:51
Gene Regulatory Networks from Single Cell Data for Exploring Cell Fate Decisionselationships. We provide guidelines on how best to combine this analysis with other complementary methods designed to explore single cell data, and how to interpret the resulting gene regulatory network models to gain insight into the processes regulating cell differentiation.作者: 新奇 時(shí)間: 2025-3-28 19:18 作者: 我不明白 時(shí)間: 2025-3-28 23:30
Lineage Inference and Stem Cell Identity Prediction Using Single-Cell RNA-Sequencing Datamajor interest. Therefore, here we present an in-house state-of-the-art scRNA-seq data analyses workflow for de novo lineage tree inference and stem cell identity prediction applicable to many biological processes under current investigation.作者: temperate 時(shí)間: 2025-3-29 06:43 作者: monologue 時(shí)間: 2025-3-29 07:21
1064-3745 ation advice from the expertsThis volume details methods and protocols to further the study of stem cells within the computational stem cell biology (CSCB) field. Chapters are divided into four sections covering the theory and practice of modeling of stem cell behavior, analyzing single cell genome-作者: lethargy 時(shí)間: 2025-3-29 14:09
Sustainable Tertiary Education in Asia strategies for building deterministic and stochastic mathematical models of gene expression and demonstrate how analysis of these models can benefit our understanding of complex observed behaviors. Developing a mathematical understanding of biological processes is of utmost importance in understanding and controlling stem cell behavior.作者: MILK 時(shí)間: 2025-3-29 16:24
https://doi.org/10.1007/978-981-10-5062-6ion (PFLI) gene circuit in the intestinal crypts. Specifically, techniques for gene circuit-driven hypothesis formation, geometry construction, selection of simulation parameters, and simulation quantification are presented.作者: 食料 時(shí)間: 2025-3-29 20:08 作者: Madrigal 時(shí)間: 2025-3-30 03:55 作者: Dysplasia 時(shí)間: 2025-3-30 06:40 作者: synchronous 時(shí)間: 2025-3-30 11:46
Agent-Based Modelling to Delineate Spatiotemporal Control Mechanisms of the Stem Cell Nicheion (PFLI) gene circuit in the intestinal crypts. Specifically, techniques for gene circuit-driven hypothesis formation, geometry construction, selection of simulation parameters, and simulation quantification are presented.作者: Exclude 時(shí)間: 2025-3-30 14:34 作者: 懸掛 時(shí)間: 2025-3-30 17:38 作者: photophobia 時(shí)間: 2025-3-31 00:46 作者: 違抗 時(shí)間: 2025-3-31 02:36 作者: arrhythmic 時(shí)間: 2025-3-31 08:09
Modeling Cellular Differentiation and Reprogramming with Gene Regulatory Networkso coordinate and maintain the overall gene expression profile observed in a cell is a key question in cellular biology. However, the immense complexity arising due to the scale and the nature of gene-gene interactions often hinders obtaining a global understanding of gene regulation. In this regard,
