Search Results for "sensitivity"
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Showing 12 open source projects for "sensitivity"
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Catalyst.jl
Chemical reaction network and systems biology interface
...Symbolic ReactionSystems can be used to generate ModelingToolkit-based models, allowing the easy simulation and parameter estimation of mass action ODE models, Chemical Langevin SDE models, stochastic chemical kinetics jump process models, and more. Generated models can be used with solvers throughout the broader SciML ecosystem, including higher-level SciML packages (e.g. for sensitivity analysis, parameter estimation, machine learning applications, etc). -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. -
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ThinkValue
Analyze stocks clearly without spending hours modeling
ThinkValue helps you analyze US stocks with clear DCF valuation models and SEC-sourced financial data. Build single or multi-stage valuations, run reverse DCFs, and test scenarios with sensitivity analysis. Use structured SEC financials via a free API, generate automated spreadsheets, and access research and KPIs on the web platform. Start free with no login or upgrade for versioned API access and integration support. -
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Notetask - Task & Notes in Plaintext
A simple application for creating and organizing task lists, offering
Notetask is a cross-platform application for managing task lists that include completion status, task description, and notes. Each task can have a due date and be marked as a favorite with a star. It uses its own storage text format based on Markdown. It is designed to help you quickly organize a large number of small routine tasks. You can enter tasks directly in the app or paste raw text from the clipboard — such as a list of requirements or ideas — then sort them into groups, set... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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PANDA
A comprehensive and flexible quantification tool for proteomics data
PANDA is a comprehensive and flexib tool for quantitative proteomics data analysis, which is developed based on our solid foundations in quantitative proteomics for years. Several novelties have been implemented in it. First, we implement the advantage algorithms of LFQuant (Proteomics 2012, 12, (23-24), 3475-84) and SILVER (Bioinformatics 2014, 30, (4), 586-7) into PANDA. Second, we consider the state-of-art concept of quantification reliability in this quantitative workflow. On the levels... -
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Financial- Math Calculator
Financial- Math Calculator
...The ‘Monte Carlo’ component can be used to run simulations in order to determine the reasons of financial uncertainty and their final effects on an investment. The ‘Sensitivity Analysis’ 1 and 2 help you discover the influence of a change in rate and number of periods over the payment. My blog: https://vegettadbz.blogspot.com/ -
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ATLAS_mPBPK
Modeling and Simulation of mPBPK models
ATLAS mPBPK is a MATLAb-based tool for modeling and Simulation of minimal Physiology Based Pharmacokinetic (mPBPK) models of small and large molecules. The tool enables the users to perform: i) PK data visualization, ii) simulation, iii) parameter optimization, and iv) local sensitivity analysis (SA) of mPBPK models in a simple and efficient manner. -
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RxCalc
RxCalc is a calculator for the analysis of multi-stage receiver.
RxCalc is a calculator for the analysis of multi-stage receiver. The software can calculate cascaded and system parameters: gain, noise, sensitivity, input and output P1dB and IP3, noise floor, spur-free dynamic range, MDS, SNR, and others. Sources code: https://github.com/arhiv6/rxcalc Binary package: http://sourceforge.net/projects/rxcalc/ -
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chipexo
model based analysis of ChIP-exo data
...MACExo has the following four steps: 1) sequencing data normalization and bias correction; 2) signal consolidation and noise reduction; 3) single nucleotide resolution border detection using Chebyshev Inequality; and 4) border matching using Gale-Shapley’s stable matching algorithm. When applied to yeast Reb1 and human CTCF ChIP-exo data, MACE is able to define TFBSs with higher sensitivity, specificity and spatial resolution, as evidenced by multiple criteria, such as motif enrichment, sequence conservation, nucleosome positioning, and open chromatin states. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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10
Linear Program Solver
Solve linear programming problems
... ● LiPS provides not just an answer, but a detailed solution process as a sequence of simplex tables, so you can use it for studying/teaching linear programming. ● LiPS gives sensitivity analysis procedures, which allow us to study the behaviour of the model when you change its parameters, including: analysis of changes in the right sides of constraints, analysis of changes in the coefficients of the objective function, analysis of changes in the column/row of the technology matrix. Such information may be extremely useful for the practical application of LP Models... -
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The Open Decision Makes enables you to find the best alternative for a defined goal with the AHP (Analytic Hierarchy Process) method.
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This is a project to model out different option scenarios using Java and price them accordingly. The hope is to take this practice out of wall street's hands and allow everyone to price and run sensitivity analysis without paying an analyst.
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