description = [ { "description": "Analyze cell migration metrics from time-lapse microscopy images.", "name": "analyze_cell_migration_metrics", "optional_parameters": [ { "default": 1.0, "description": "Conversion factor from pixels to micrometers", "name": "pixel_size_um", "type": "float", }, { "default": 1.0, "description": "Time interval between consecutive frames in minutes", "name": "time_interval_min", "type": "float", }, { "default": 10, "description": "Minimum number of frames a cell must be tracked to be included in analysis", "name": "min_track_length", "type": "int", }, { "default": "./", "description": "Directory to save output files", "name": "output_dir", "type": "str", }, ], "required_parameters": [ { "default": None, "description": "Path to the directory containing time-lapse images or path to a multi-frame TIFF file", "name": "image_sequence_path", "type": "str", } ], }, { "description": "Simulates CRISPR-Cas9 genome editing process including guide " "RNA design, delivery, and analysis.", "name": "perform_crispr_cas9_genome_editing", "optional_parameters": [], "required_parameters": [ { "default": None, "description": "List of guide RNA sequences (20 " "nucleotides each) targeting the " "genomic region of interest", "name": "guide_rna_sequences", "type": "List[str]", }, { "default": None, "description": "Target genomic sequence to be " "edited (should be longer than guide " "RNA and contain the target sites)", "name": "target_genomic_loci", "type": "str", }, { "default": None, "description": "Type of cell or tissue being edited (affects delivery efficiency and editing outcomes)", "name": "cell_tissue_type", "type": "str", }, ], }, { "description": "Analyze calcium imaging data to quantify neuronal activity " "metrics including cell counts, event rates, decay times, and " "signal-to-noise ratios.", "name": "analyze_calcium_imaging_data", "optional_parameters": [ { "default": "./", "description": "Directory to save output files", "name": "output_dir", "type": "str", } ], "required_parameters": [ { "default": None, "description": "Path to the time-series stack of fluorescence microscopy images (TIFF format)", "name": "image_stack_path", "type": "str", } ], }, { "description": "Analyzes in vitro drug release kinetics from biomaterial formulations.", "name": "analyze_in_vitro_drug_release_kinetics", "optional_parameters": [ { "default": "Drug", "description": "Name of the drug being analyzed", "name": "drug_name", "type": "str", }, { "default": None, "description": "Total amount of drug initially " "loaded in the formulation. If None, " "the maximum concentration is used " "as 100%", "name": "total_drug_loaded", "type": "float", }, { "default": "./", "description": "Directory to save output files", "name": "output_dir", "type": "str", }, ], "required_parameters": [ { "default": None, "description": "Time points at which drug concentrations were measured (in hours)", "name": "time_points", "type": "List[float] or numpy.ndarray", }, { "default": None, "description": "Measured drug concentration at each time point", "name": "concentration_data", "type": "List[float] or numpy.ndarray", }, ], }, { "description": "Quantifies morphological properties of myofibers in microscopy images of tissue sections.", "name": "analyze_myofiber_morphology", "optional_parameters": [ { "default": 2, "description": "Channel index containing nuclei staining (DAPI, Hoechst, etc.)", "name": "nuclei_channel", "type": "int", }, { "default": 1, "description": "Channel index containing myofiber staining (α-Actinin, etc.)", "name": "myofiber_channel", "type": "int", }, { "default": "otsu", "description": "Method for thresholding ('otsu', 'adaptive', or 'manual')", "name": "threshold_method", "type": "str", }, { "default": "./", "description": "Directory to save output files", "name": "output_dir", "type": "str", }, ], "required_parameters": [ { "default": None, "description": "Path to the microscopy image file " "(typically a multichannel image " "with nuclei and myofiber staining)", "name": "image_path", "type": "str", } ], }, { "description": "Model neural activity trajectories and decode behavioral variables.", "name": "decode_behavior_from_neural_trajectories", "optional_parameters": [ { "default": 10, "description": "Number of principal components to use for dimensionality reduction", "name": "n_components", "type": "int", }, { "default": "./", "description": "Directory to save output files", "name": "output_dir", "type": "str", }, ], "required_parameters": [ { "default": None, "description": "Neural spiking activity data, shape (n_timepoints, n_neurons)", "name": "neural_data", "type": "numpy.ndarray", }, { "default": None, "description": "Behavioral data, shape (n_timepoints, n_behavioral_variables)", "name": "behavioral_data", "type": "numpy.ndarray", }, ], }, { "description": "Simulate a whole-cell model represented as a system of ordinary differential equations (ODEs).", "name": "simulate_whole_cell_ode_model", "optional_parameters": [ { "default": None, "description": "Function defining the system of " "ODEs. Should take arguments (t, y, " "*args) where t is time, y is the " "state vector, and args contains " "additional parameters. If None, a " "simple example whole-cell model " "will be used.", "name": "ode_function", "type": "callable", }, { "default": "(0, 100)", "description": "Tuple of (start_time, end_time) for the simulation.", "name": "time_span", "type": "tuple", }, { "default": 1000, "description": "Number of time points to evaluate.", "name": "time_points", "type": "int", }, { "default": "'LSODA'", "description": "Numerical integration method to use (e.g., 'RK45', 'LSODA', 'BDF').", "name": "method", "type": "str", }, ], "required_parameters": [ { "default": None, "description": "Initial values for each state " "variable in the model. If dict, " "keys are variable names and values " "are initial concentrations/values. " "If array-like, order must match the " "order expected by the ODE function.", "name": "initial_conditions", "type": "dict or array-like", }, { "default": None, "description": "Model parameters required by the " "ODE function. Keys are parameter " "names and values are parameter " "values.", "name": "parameters", "type": "dict", }, ], }, ]