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/ / Quantitative mathematical modelling of the alternative pathway of the complement system

Quantitative mathematical modelling of the alternative pathway of the complement system

A. Tille, T. Lehnert, P. Zipfel, M. T. Figge

Modeling M-12

01/05/2017

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In silico Experiments of Fungal and Bacterial Infections in Virtual Neutropenic Patients suggest Optimal Treatment Strategies
Automated tracking and characterization of cell dynamics for classifier models

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Posters ASB-82458 Deep learning supported image analysis of angle-resolved scattered light images of bacteria in microfluidic droplets

ASB-82457 A spatio-temporal model for simulating hyphal growth of filamentous fungal species

IA-68 JIPipe: Designing automated image analysis
pipelines without programming

IbSB-13 Mcat: a multispectral cluster analysis toolkit for deep learning-based segmentation and clinical biomarker quantification of MSOT data

M-40 Modeling Candida albicans Complement Regulator Pra1

IA-67 Automated Characterization of Neutrophil Activation Phenotypes for Human Candida Bloodstream Infections

IA-62 AMIT: A high performance segmentation and tracking framework for migration and confrontation assays

IA-63 Automatic segmentation and classification of fungal-infected tissue using Deep Learning

IA-61 3D-HyTracer: Quantitative hyphal growth analysis through hyphae-to-graph transormation

IA-66 Machine learning supported image analysis of microfluidic droplets

IA-65 Algorithm for confrontation assay quantification (ACAQ): Label-free image analysis supported by Hessian filtering

IA-64 From raw images to abstract surface models: deconvolution, DeConvTest and DynSPHARM

IA-58 MISA++: A standardized interface for automated bioimage analysis

IA-57 JIPipe: Designing automated image analysis pipelines without programming

M-36 Virtual whole-blood infection assays

IbSB-12 Causal inference analysis of live cell imaged confrontation
assays with agent-based modelling

IbSB-10 Research Group Applied Systems Biology

IbSB-9 Leibniz ScienceCampus InfectoOptics - Combating infectious diseases with advanced optical methods

IA-60 Mcat: A toolkit for deep learning-based segmentation and automated analysis of MSOT image data

IA-59 Methods for quantitative analysis of bone degradation and remodeling from μCT images

M-37 Studies on virtual whole-blood infection assays

M-39 Design of an optimal COVID-19 surveillance protocol for child care facilities using an infection spread model

M-35 Comparative simulations of fungal infection dynamics in the human and murine lung

M-38 DynaCoSys: Dynamic model of the complement system to understand pathogen immune evasion

M-34 Hybrid agent-based modeling framework to simulate A. fumigatus infection scenario in the lung

IA-56 JIPipe: Designing automated image analysis pipelines without programming

IbSB-11 Virtual phagocytosis assays reveal strain‐speciﬁc diﬀerences in the microscopic parameters of the interaction between alveolar macrophages and two A. fumigatus strains

IA-54 MSOT cluster analysis toolkit to objectively assess pharmacokinetics and biodistribution of clinical biomarkers

IA-52 MISA++: a standardized interface for automatedhigh-performance big volume image analysis

IA-55 Quantitative image analysis of label-free cells

IbSB-8 Virtual phagocytosis assays reveal strain‐speciﬁc differences in the microscopic parameters of the interaction between alveolar macrophages and two A. fumigatus strains

IA-53 Morphokinetic analysis of live-cell imaging data

M-31 Simulation of virtual phagocytosis assays with alveolar macrophages and Aspergillus fumigatus conidia

M-33 Quantification of the dynamics of fungal confrontation assays

M-32 Quantification of factor H mediated self and non-self discrimination by mathematical modeling

IA-51 Automated Analysis of Fungal-Infected Tissue using Deep Learning

M-30 Verifying Hypotheses on Immune Evasion by Pathogens in Human Whole Blood by State-based Virtual Infection Models

IA-50 DeconvTest: an in silico microscopy framework to evaluate the accuracy of deconvolution

M-28 Quantitative Simulations Predict Treatment Strategies Against Fungal Infections in Virtual Neutropenic Patients Fungal Infections in Virtual Neutropenic Patients

IA-49 B4: Cause - Effect Relationships in Confrontation Assays with C. glabrata and Human Neutrophils using Bayesian Networks

M-29 Agent-based modeling of early Aspergillus fumigatus infection in mice

M-27 Mathematical model of the factor H mediated self and non-self discrimination by the complement system

IbSB-4 Simulation of virtual phagocytosis assays with alveolar marcrophages and Aspergillus fumigatus conidia reveals immune reaction rates

IA-44 Towards an open high-performance platform for fully-automated analysis of whole organ light-sheet fluorescence microscopy data

IA-37 DeconvTest: An in silico microscopy framework to evaluate the accuracy of deconvolution

IA-40 ACAQ: a Fiji and R toolkit targeted for automated confrontation assay quantification

IA-43 Measured and simulated 3D spatial distribution of plasma cells in the mouse bone marrow

M-22 Virtual Infection Modeling of the Early Immune Response to Fungal Infections in Murine Whole Blood

IA-42 Combining whole-blood infection assays with life-cell imaging to identify morphokinetic parameters for infection classification

M-24 Mathematical model of the factor H mediated self and non-self discrimination by the complement system

M-25 Agent-based modeling of early Aspergillus fumigatus infection in mice

IA-33 Fast and efficient fully automated processing of lightsheet microscopy data to evaluate the glomerular number in kidneys

IA-34 Automated image analysis methods for the quantification of cell damage and adherent fungal cells

M-21 Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood

M-26 Agent-based modeling of early Aspergillus fumigatus infection in mice

IA-41 Joint Intravital Microscopy and Imaging: a multi-institute collaborative platform to aid intravital microscopy

IA-36 Cell tracking of Neutrophils in Phagocytosis Assays

IA-35 Image Processing in Droplet Microfluidics

IA-39 Quantitative analysis of intracellular communication from life cell imaging

IA-47 Analysis of Dynamic Properties in Biological Systems from Image Data

IA-32 Machine learning supported image analysis of microfluidic droplets: Using Random Forest classifiers and Bayesian inference for identification of experimental conditions

IbSB-2 ICH SEHE WAS, WAS DU NICHT SIEHST: BILDANALYSE UND COMPUTERSIMULATIONEN FÜR DIE INFEKTIONSDIAGNOSTIK

IA-38 Lang Nacht der Wissenschaften - Lichtblattfluorescencemikroscopie (LSFM)

M-15 Predictions of antimicrobial treatment strategies based on in silico experiments of virtual neutropenic patients

IA-27 Morphokinetic analysis of neutrophils from whole-blood infection assays

M-19 Quantification of the innate immune function in whole-blood infection assays reveals pathogen-dependent immune defence of different sepsis phases

M-20 Quantification of Innate Immune Function in Whole-blood Infection Assays

M-13 Agent-based modeling of early Aspergillus fumigatus infection in mice

IA-29 Automated Image Analysis of the Interaction between Lichtheimia spp. and Alveolar Macrophages

IA-30 Multispectral optoacoustic tomography to assess liver and kidney function in sepsis by measuring dye clearance

M-14 Predictive Virtual Infection Modeling of Pathogenic Immune Evasion in Human Whole-blood

M-23 Quantitative virtual infection modeling in sepsis

IA-25 Automated tracking and characterization of cell dynamics for classifier models

M-12 Quantitative mathematical modelling of the alternative pathway of the complement system

M-16 In silico Experiments of Fungal and Bacterial Infections in Virtual Neutropenic Patients suggest Optimal Treatment Strategies

IA-45 Enhanced Detection of Unstained Cells in an Existing Segmentation and Tracking Framework

IA-28 Migration and Interaction Tracking for Quantitative Analysis of Phagocyte‐Pathogen Confrontation Assays

M-17 QUANTIM- Quantification of Innate Immune Function in Whole Blood Infection Assay

IA-26 Automated tracking and characterization of cell dynamics for classifier models

IbSB-6 B4: Image data analysis and agent-based modelling of the spatio-temporal interaction between immune cells and human-pathogenic fungi

IA-31 In vivo quantification of arthritis-induced alterations of murine bones based on PET/CT image data

IA-20 Enhanced Detection of Unstained Cells in an Existing Segmentation and Tracking Framework

IA-18 Track-based analysis of cell migration

M-18 Dimensionality of motion and binding valency govern receptor-ligand kinetics as revealed by agent-based modelling

M-11 Investigating Candida albicans resistance in whole-blood assays by virtual infection models using parallelized parameter estimation

IA-15 Morphological restoration: A fast alternative to deconvolution of cells in 3D images

IA-19 Enhanced Detection of Unstained Cells in an Existing Segmentation and Tracking Framework

IA-24 Striped Illumination Microscopy with an enhanced iterative processing algorithm provides a novel high-resolution deep-tissue imaging technique

IA-17 Automated enumeration of circulating tumor cells: machine learning techniques and interobserver variability

IA-16 Combined [18F]-Fluoride Imaging in Experimental Arthritis

IA-23 Image Segmentation Methods for the Quantification of C. albicans cells in Fluorescence Images

M-10 Virtual infection model for Aspergillus fumigatus in human alveoli

IA-22 Image Segmentation Methods for the Quantification of C. albicans cells in Fluorescence Images

IA-21 AMIT: a novel algorithm for migration and interaction tracking for high-throughput analysis of phagocytosis assays

IbSB-3 Angewandte Systembiologie

IA-13 Automated Characterization of Cell Tracks: Step forward

M-9 Simulation of Immune Cell Deficiencies in a State-based Virtual Infectin Model of Human Whole-blood Assays for Candida albicans

M-8 Investigation of spatial dynamics of fungal-host-interactions of Candida albicans and innate immune cells

IA-14 Automated Image Analysis for Quantifying Fungus-host Interactions

M-7 Hybrid agent-based modeling of human alveoli reveals chemokine properties in Aspergillus fumigatus infection

M-5 Agent-based Modeling on Cellular and Molecular Scales

M-6 Virtual Infection Models of Candida albicans in Whole Blood

IbSB-1 Epithelial Invasion Outcompetes Hypha Development During Candida albicans Infection as Revealed by an Image-based Systems Biology Approach

M-4 A hybrid agent-based modeling approach of Aspergillus fumigatus infection in the human alveolus

IA-7 Automated Detection of Circulating Tumour Cells

IA-10 Automated Image Analysis of Microfluidic Droplets

IA-8 Automated image analysis of the host-pathogen interaction between immune cells and human-pathogenic fungi

IA-5 Image analysis of immune cell interactions from two-photon microscopy dat

IA-6 In vivo Quantiﬁcation of Arthritis Severity in a Murine Model by µCT Imaging

IA-11 Quantitative image analysis of cell colocalization in murine bone marrow

IA-12 Automated characterization of cell tracks based on local migration behavior

IA-9 Comparative Study of Phagocytosis-assays for Lichtheimia Species by Automated Analysis of Fluorescence Microscopy Images

IA-4 Automated characterization of cell tracks based on local migration behavior

M-3 Virtual infection model of the immune response against Candida albicans in human whole-blood assay

IA-3 Quantiﬁcation of Arthritis Progression From CT Images

IA-2 Automated Detection of Circulating Tumour Cells

IA-46 Image Processing in Droplet Microfluidics

M-2 Parameter Estimation by Simulated Annealing for Models of Whole-Blood Infection Assays with Candida Albicans

M-1 A Spatio-Temporal Modeling Framework to Simulate Host-Pathogen Interaction

IA-1 Single Cell Track Analysis of Two Photon Microscopy on Th17 Cells in the Gut

IA-48 Automated Image Analysis of the Interaction between Phagocytes and Aspergillus fumigatus during infection

IbSB-5 Quantitative description of fungal morphology by automated image analysis

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