[go: up one dir, main page]

Angaroni et al., 2025 - Google Patents

Translating microbial kinetics into quantitative responses and testable hypotheses using Kinbiont

Angaroni et al., 2025

View HTML @Full View
Document ID
7989084596733620905
Author
Angaroni F
Peruzzi A
Alvarenga E
Pinheiro F
Publication year
Publication venue
Nature Communications

External Links

Snippet

Challenges such as antibiotic resistance, ecosystem resilience, and bioproduction optimization require quantitative methods to characterize microbial responses to environmental perturbations. However, translating rapidly growing microbial growth datasets …
Continue reading at www.nature.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587—Details of specialised database models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20—Handling natural language data
    • G06F17/21—Text processing
    • G06F17/24—Editing, e.g. insert/delete
    • G06F17/246—Spreadsheets
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/24—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/20—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for hybridisation or gene expression, e.g. microarrays, sequencing by hybridisation, normalisation, profiling, noise correction models, expression ratio estimation, probe design or probe optimisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/22—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/70—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
    • G06F19/702—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for analysis and planning of chemical reactions and syntheses, e.g. synthesis design, reaction prediction, mechanism elucidation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines

Similar Documents

Publication Publication Date Title
Culley et al. A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth
Narayanan et al. A new generation of predictive models: The added value of hybrid models for manufacturing processes of therapeutic proteins
Thomas et al. Sources, propagation and consequences of stochasticity in cellular growth
Charlebois et al. Modeling cell population dynamics
Oyetunde et al. Machine learning framework for assessment of microbial factory performance
Choudhury et al. Reconstructing kinetic models for dynamical studies of metabolism using generative adversarial networks
Szappanos et al. An integrated approach to characterize genetic interaction networks in yeast metabolism
Chechik et al. Activity motifs reveal principles of timing in transcriptional control of the yeast metabolic network
Brooks et al. Challenges and best practices in omics benchmarking
Greene et al. Acceleration strategies to enhance metabolic ensemble modeling performance
Klein et al. Evolution and emergence: higher order information structure in protein interactomes across the tree of life
Žitnik et al. Gene prioritization by compressive data fusion and chaining
Rodman et al. Parameter estimation and sensitivity analysis for dynamic modelling and simulation of beer fermentation
Tan et al. ADAGE signature analysis: differential expression analysis with data-defined gene sets
van Heck et al. Efficient reconstruction of predictive consensus metabolic network models
Damiani et al. An ensemble evolutionary constraint-based approach to understand the emergence of metabolic phenotypes
Bhadra et al. Principal metabolic flux mode analysis
Ji et al. Optimal distance metrics for single-cell RNA-seq populations
Choi et al. Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations
Heintz-Buschart et al. A beginner’s guide to integrating multi-omics data from microbial communities
Huttenhower et al. The impact of incomplete knowledge on evaluation: an experimental benchmark for protein function prediction
Lei et al. An approach of gene regulatory network construction using mixed entropy optimizing context-related likelihood mutual information
Gustafsson et al. Gene expression prediction by soft integration and the Elastic Net—Best performance of the DREAM3 gene expression challenge
Turek et al. OmicsON–Integration of omics data with molecular networks and statistical procedures
Angaroni et al. Translating microbial kinetics into quantitative responses and testable hypotheses using Kinbiont