TALK KEYWORD INDEX
This page contains an index consisting of author-provided keywords.
| 1 | |
| 13C metabolic flux analysis | |
| 13C MFA | |
| A | |
| ABC | |
| actin | |
| actinobacteria | |
| activation threshold | |
| Adaptation | |
| Adult stem cell | |
| ageing | |
| Ageing strategy | |
| algorithms | |
| Amyloid | |
| analog computing | |
| Analysis | |
| Anaphase regulatory proteins | |
| Anti-cancer drug | |
| antibiotic resistance | |
| antibiotics | |
| Antimicrobials | |
| apoptosis | |
| Arabidopsis | |
| Arabidopsis thaliana | |
| arrhythmia | |
| artificial neural network | |
| ATAC-seq | |
| Atomic force microscopy | |
| Attractor landscape | |
| Attractors | |
| automated experimental planning | |
| Autonomous Oscillations | |
| auxotrophy predictions | |
| B | |
| B. licheniformis | |
| bacteria | |
| Bacterial conjugation | |
| bacterial pathogens | |
| bar-code deletion library | |
| Barcode | |
| bifurcation | |
| bifurcation analysis | |
| bifurcation theory | |
| Biochemical Modeling | |
| Biochemical networks | |
| bioinformatics | |
| Biological networks | |
| biological noise | |
| Biological oscillators | |
| biomarker identification | |
| bioproduction | |
| Biosensor | |
| Bistability | |
| bistable switch | |
| bistable switches | |
| black box model | |
| blood pressure regulation | |
| BMP signaling | |
| BOLD response | |
| boolean model | |
| Boolean Modeling | |
| Boolean modeling and simulation | |
| Boolean network | |
| bottleneck | |
| Bottom Up | |
| BPA | |
| Breast cancer | |
| Budding Yeast | |
| budding yeast cell cycle model | |
| Bullous Pemphigoid | |
| bursts | |
| C | |
| c-MYC | |
| C. elegans | |
| CAD | |
| Caenorhabditis elegans | |
| cameo | |
| cancer | |
| cancer biomarker | |
| Cancer biomarkers | |
| Cancer cell line | |
| Cancer cell lines | |
| cancer classification | |
| Cancer development | |
| Cancer drugs | |
| Cancer evolution | |
| cancer initiation | |
| Cancer Phenotype | |
| Cancer signalling | |
| cancer systems biology | |
| cancer treatment | |
| Carcinogenesis | |
| Caulobacter Cell Cycle | |
| CD4+ T-cell differentiation | |
| CDK inhibitors | |
| cell cycle | |
| cell cycle checkpoints | |
| Cell Cycle Control | |
| cell cycle regulation | |
| cell cycles | |
| cell division | |
| Cell factories | |
| Cell fate decision | |
| cell growth | |
| cell mass quantification | |
| cell polarity | |
| cell signaling | |
| Cell size | |
| cell size control | |
| Cell-cell adhesion | |
| CellDesigner | |
| cellular death | |
| cellular heterogeneities | |
| Cellular Signaling | |
| Cellular signalling networks | |
| Cellular Signalling Pathway | |
| cellular survival | |
| cellular variability | |
| chemotaxis | |
| chemotropsim | |
| Circadian clock | |
| circadian rhythm | |
| cloud computing | |
| Clustering | |
| Clustering Biological Systems | |
| co-expression quasicliques | |
| co-infection | |
| Co-receptor CD8 | |
| Co-regulation | |
| Co-target identification | |
| cobra | |
| cobrapy | |
| collaborations | |
| Combination Therapy | |
| combinatorial perturbations | |
| Combinatorial signal processing | |
| Combine | |
| comet tails | |
| comparative omic analysis | |
| Comparing correlation matrices | |
| Compartmentalized Metabolic Engineering | |
| Compartmentalized signaling | |
| Complex systems | |
| Computational | |
| computational biology | |
| Computational cancer biology | |
| Computational Model | |
| computational modeling | |
| Computational models | |
| computational simulation | |
| computer simulation | |
| connections between courses | |
| constraint based modeling | |
| constraint-based modeling | |
| constraints | |
| constraints-based models | |
| Control theory | |
| COPASI | |
| Coupled oscillator | |
| CRISPR | |
| crosstalk | |
| Curriculum | |
| Cytokines | |
| cytoskeleton | |
| D | |
| Damage accumulation theory | |
| Damage retention | |
| Data aggregation | |
| Data integration | |
| Data management | |
| database | |
| Databases | |
| Dauer | |
| Decay rates | |
| decision-support | |
| deep learning | |
| Deterministic | |
| developing tutorials | |
| Development | |
| Differentiation | |
| diffusion | |
| Discrete dynamic model | |
| Disease | |
| Division | |
| DNA construct | |
| DNA damage response | |
| DNA Replication | |
| Drug combination | |
| Drug response | |
| Drug response prediction | |
| Drug sensitivity | |
| drug simulations | |
| Drug transport | |
| dwSSA | |
| Dynamic modelling | |
| Dynamic stability | |
| Dynamical analysis | |
| dynamical modeling | |
| dynamical models | |
| Dynamical systems | |
| dynamical systems theory | |
| Dynamics | |
| dynamics treatment design | |
| E | |
| E. coli | |
| early developmental embryos | |
| Ecological dynamics | |
| education | |
| Efficient chemotactic performance | |
| Elastic Net | |
| Elementary modes | |
| Emulating mechanism-based models | |
| Endocrine therapies resistance | |
| Energy landscape analysis | |
| enhancer | |
| Enhancer landscape | |
| ensemble of single cell models | |
| enzyme | |
| Enzyme promiscuity | |
| Epigenetic regulatory network | |
| Epigenetics | |
| Epithelial-mesenchymal plasticity | |
| ER+ breast cancer | |
| Error models | |
| escher | |
| Eukaryotes | |
| evolution | |
| experiment planning | |
| Experimental design | |
| experimental validation | |
| Extracellular Matrix | |
| Extreme pathways | |
| F | |
| FAIRDOM | |
| Fatty acid synthesis | |
| fatty alcohols | |
| feed-forward loops | |
| feedback | |
| feedback regulation | |
| fibrosis | |
| filopodia | |
| Fisher information | |
| fission yeast | |
| flipped classroom | |
| flow cytometry | |
| Fluctuation in signalling pathway | |
| fluorescence protein tagging | |
| Flux Balance Analysis | |
| Flux-balance analysis | |
| Fluxomics | |
| Folate pathway | |
| four-dimensional microscopic image | |
| Fractional Killing | |
| FRET biosensor | |
| Functional genomics | |
| G | |
| G protein-coupled receptor | |
| G2 checkpoint | |
| gapfilling algorithms based on phylogeny | |
| GEF-H1 | |
| gene expression | |
| Gene expression prediction | |
| Gene networks | |
| gene regulation | |
| gene regulatory networks | |
| Genetic Circuit | |
| genetic crosses | |
| Genetic regulation | |
| Genome mining | |
| Genome scale metabolic modeling | |
| Genome scale model | |
| Genome-scale metabolic models | |
| Genome-scale model | |
| genome-scale modeling | |
| genomic instability | |
| Genotype-phenotype | |
| Gillespie's stochastic simulation algorithm | |
| glioblastoma | |
| GO semantic similarity | |
| GPU | |
| gradients | |
| graphs | |
| growth rate modulation | |
| Gut microbiome | |
| Gut microbiota | |
| H | |
| H2O2 | |
| half lifes | |
| HBsAg | |
| Hematopoiesis | |
| Heparin Hydrogel | |
| Hepcidin | |
| Heterogeneity | |
| high performance computing | |
| high-throughput experiments | |
| Hilbert-Huang transform | |
| host-pathogen | |
| Host-pathogen dynamics | |
| HPV | |
| HRS/IRR | |
| hume genome | |
| Hybrid epithelial/mesenchymal | |
| hybrid modelling | |
| hybrid ODE/SSA method | |
| Hypergraph | |
| Hyperpath | |
| hysteresis | |
| I | |
| iBioSim | |
| IGF1 | |
| image analysis | |
| image processing | |
| immune response | |
| immune system | |
| Immunology | |
| in vivo | |
| Infectious Diseases | |
| information | |
| information theory | |
| Innate Immunology | |
| Insulin | |
| Interactome | |
| Interdependency | |
| Interdisciplinary education | |
| interferons | |
| Intestinal stem cells | |
| intrinsic stochasticity | |
| Iron metabolism | |
| Isoform | |
| isoprenoids | |
| J | |
| JWS Online | |
| K | |
| KaiABC | |
| kcat | |
| KEGG | |
| Key words | |
| Killer | |
| kinetic constants | |
| Kinetic data | |
| kinetic model | |
| kinetics | |
| kockin | |
| L | |
| Large scale dynamical modelling | |
| large-scale analysis using KBase | |
| LCC1 | |
| LCC9 | |
| Lesion-like brain disorder | |
| Ligand discrimination | |
| lignin biosynthetic pathway | |
| linear system approximation modeling | |
| Lipopeptides | |
| local communication | |
| logical modeling | |
| low-dose radiation | |
| M | |
| machine learning | |
| Malnutrition | |
| Manatee invariants | |
| Markov Chain Monte Carlo | |
| Master Regulators | |
| Master's and bachelor degrees | |
| Mathematical Epidemiology | |
| Mathematical Mdodeling | |
| Mathematical Model | |
| mathematical modeling | |
| Mathematical modelling | |
| Maximum entropy model | |
| MCF7 | |
| Mechanistic modeling | |
| MEG | |
| melanoma | |
| membrane tension | |
| Menthol biosynthesis | |
| Merged state transition map | |
| Meta-genomics | |
| metabolic | |
| metabolic adaptation | |
| Metabolic control analysis | |
| metabolic engineering | |
| Metabolic model | |
| Metabolic modeling | |
| metabolic modelling | |
| Metabolic network | |
| Metabolic networks | |
| Metabolic reconstruction | |
| Metabolism | |
| Metabolomics | |
| Methanotrophy | |
| Methotrexate resistance | |
| microalgae | |
| Microarray | |
| microarray gene expression | |
| Microbial ecology | |
| microbial phenotypes | |
| Microbiome | |
| Microfluidic Device | |
| Microfluidics | |
| Microscopy | |
| microtubule disassembly | |
| Minardo web tool | |
| minimal Cdk network | |
| Minimal cell | |
| minimize computational cost | |
| minimum dominating set | |
| MIRIAM | |
| miRNA | |
| Missing Protein | |
| Mitophagy in human | |
| mitosis | |
| mitotic checkpoint | |
| model discrimination | |
| Model fitting | |
| model integration | |
| Model reduction | |
| Model selection | |
| Model simulation | |
| modeling | |
| Modelling | |
| Modelling standards | |
| Modelling tools | |
| models | |
| Modular Response Analysis | |
| Molecular networks | |
| Monte Carlo Simulation | |
| Morphodynamic profiling | |
| morphology | |
| mRNA dynamics | |
| multi-algorithm | |
| multi-cellular model | |
| multi-omics integration | |
| multi-scale | |
| Multicellular Systems Biology | |
| Multiple Phase Interlocker | |
| multiple-objective optimization | |
| Multistable Dynamics | |
| multivalency | |
| muscle atrophy | |
| Mycoplasma mycoides | |
| Myeloid-Derived Suppressor Cells | |
| N | |
| network attack simulation | |
| Network communicability | |
| Network control | |
| Network Dynamics | |
| Network entropy | |
| Network inference | |
| network model | |
| network motifs | |
| Network reduction | |
| network structures and motifs | |
| Network switch | |
| Network topology | |
| networks | |
| Neural development | |
| Neural Networks | |
| Neuropeptide | |
| Neutrophil | |
| Noise | |
| noise in gene expression | |
| Non-linear Dynamics | |
| Non-targeted metabolomics | |
| NRPs | |
| NTBI | |
| nutrient signaling | |
| O | |
| ODE modelling | |
| olfaction | |
| Oncogenic Signaling Pathway | |
| optimistic | |
| optimization | |
| Optogenetic perturbation | |
| Optogenetics | |
| Organoid | |
| P | |
| P-invariant | |
| p53 regulation | |
| pairwise interactions | |
| parallel discrete event simulation | |
| Parameter Estimation | |
| Parameter Sensitivity | |
| Parameter uncertainty | |
| parametric space exploration | |
| Parasitic Nematodes | |
| Pathway analysis | |
| pattern detection | |
| Pattern formation | |
| Peroxiporins | |
| Peroxisome | |
| persister | |
| Petri net | |
| Pharmacological Ascorbate | |
| Pharmacology | |
| phase field model | |
| phase plane analysis | |
| Phenotype transition | |
| Phenotypic attractors | |
| Phenotypic network | |
| Phenotyping | |
| Phosphoproteomic time series datasets | |
| Phosphoproteomics | |
| photosynthesis | |
| Physiology | |
| plasmid | |
| Poisson Point Process | |
| Polarity establishment | |
| population dynamics | |
| positive feedback loops | |
| post-transcription | |
| Precision medicine | |
| predicting the perturbation effects | |
| Prey | |
| professional development | |
| programming | |
| proliferating mammalian cell | |
| proliferation | |
| Prostate Cancer | |
| protease | |
| Protein aggregation | |
| Protein assembly | |
| Protein design | |
| protein express pathway | |
| Protein interaction network | |
| Protein Interaction Networks | |
| Protein-protein interaction | |
| Proteogenomics | |
| Proteomics | |
| python | |
| Q | |
| Quantitative biology | |
| quantitative phase microscopy | |
| Quantitative Systems Pharmacology | |
| queueing theory | |
| quiescence | |
| R | |
| radiogenomics | |
| rare event | |
| Rb-E2F bistable switch network | |
| Rb-E2F pathway | |
| reaction | |
| reaction diffusion | |
| reaction networks | |
| real scientific B.Sc. projects | |
| Regularized linear regression | |
| regularized regression models | |
| Regulatory Network | |
| Regulatory network topology | |
| Replication | |
| Replicative life span | |
| Resting-state network | |
| restriction enzyme | |
| Reverse-engineering | |
| Rho-GTPase | |
| RhoA GTPase | |
| Ribo-Seq | |
| ribosome profiling | |
| RNA Regulatory strategies | |
| RNA splicing | |
| RNA virus | |
| RNA-seq | |
| RNA-sequencing | |
| robustness | |
| robustness of temporal order | |
| S | |
| S. cerevisiae | |
| SABIO-RK | |
| Saccharomyces cerevisiae | |
| SBGN | |
| SBML | |
| Scaling | |
| SED-ML | |
| self-renewal | |
| sense-antisense transcripts interactions | |
| Sensitivity Analysis | |
| Sepsis | |
| service | |
| Shape formation | |
| signal transduction | |
| Signal transduction pathways | |
| Signaling | |
| Signaling Network | |
| Signalling pathway | |
| signalling pathways | |
| simulation | |
| Simulation tools | |
| single cell | |
| Single cell chemotaxis | |
| Single cell dynamics | |
| Single cell protein | |
| single-cell biology | |
| Single-cell dynamics | |
| Single-Cell Fate Mapping | |
| SIR models | |
| Skin | |
| SLCs | |
| small cell lunger cancer | |
| smFISH | |
| snap-shot data | |
| Software | |
| Software Tool | |
| SParSE++ | |
| Spatial mathematical modeling | |
| Spatial Stochastic Simulation | |
| spatially-resolved eukaryotic cell models | |
| Spatio-temporal | |
| spatiotemporal model | |
| Spectral decomposition | |
| Spindle assembly checkpoint | |
| SSA | |
| Stable Motif | |
| Standards | |
| Start transition | |
| stationary phase | |
| Statistical region merging | |
| Steady state analysis | |
| Stem Cell | |
| Stochastic | |
| stochastic modeling | |
| stochastic modelling | |
| Stochastic Simulation | |
| stochastic simulation algorithm (SSA) | |
| Streptomyces | |
| Stress | |
| Structural identifiability | |
| Synergistic control targets | |
| Synergy | |
| synthetic biology | |
| System Biology | |
| system dynamics | |
| system identification | |
| systems biology | |
| systems biology education | |
| Systems Biology of Herbal Medicine | |
| Systems immunology | |
| systems medicine | |
| Systems neuroscience | |
| systems pharmacology | |
| Systems’ structures and functions | |
| T | |
| T cell activation | |
| T Cell Differentiation | |
| T helper 22 cell | |
| T-cell differentiation plasticity | |
| T-helper cells | |
| T-invariant | |
| Targeted metabolomics | |
| Temporally ordered progression | |
| testing | |
| Threshold Boolean Networks | |
| Time Course Clustering | |
| Timing | |
| tissue patterning | |
| TNF signaling | |
| Top Down | |
| Toxicology | |
| toxin-antitoxin systems | |
| tradeoff | |
| Traditional Japanese medicine (Kampo) | |
| Traditional Japanese medicine(Kampo) | |
| transcription | |
| Transcriptional burst | |
| transcriptional regulatory network | |
| Transcriptional regulatory network inference | |
| Transcriptomics | |
| Transient Oscillations | |
| Transition invariants | |
| Trasncription rates | |
| Tumor dynamics | |
| Tumor microenvironment | |
| Tumor suppressor p53 | |
| Tumor-Specific Combination Therapy | |
| Tumor-stromal interactions | |
| turing | |
| Turing pattern formation | |
| turnover number | |
| Two-phase dynamics | |
| U | |
| undergraduate degree | |
| undergraduate research | |
| unfair competition | |
| Unfolded protein response | |
| Unicellular ageing | |
| V | |
| Variant | |
| Virtual Cell | |
| viruses | |
| Visualization | |
| W | |
| wave pinning model | |
| Waves of Cyclins | |
| web-based | |
| WGCNA | |
| whole-brain structural network | |
| Whole-cell simulations | |
| Wnt | |
| workflow | |
| wSSA | |
| X | |
| xylose | |
| Y | |
| yeast | |
| yeast genetics | |
| Yeast knockout | |
| “ | |
| “Snake vectors” | |