Tag: Parameter

Data2Dynamics 170117 – Modeling Environment Tailored to Parameter Estimation in Dynamical System

Data2Dynamics 170117

:: DESCRIPTION

The Data2Dynamics software package is a collection of numerical methods for quantitative dynamic modeling and a comprehensive model and data description language. The software facilitates the construction of dynamical models for biochemical reaction networks, but is not limited to this.

::DEVELOPER

D2D development team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • MatLab

:: DOWNLOAD

 Data2Dynamics

:: MORE INFORMATION

Citation:

Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems.
Raue A, Steiert B, Schelker M, Kreutz C, Maiwald T, Hass H, Vanlier J, T?nsing C, Adlung L, Engesser R, Mader W, Heinemann T, Hasenauer J, Schilling M, H?fer T, Klipp E, Theis F, Klingmüller U, Sch?berl B, Timmer J.
Bioinformatics. 2015 Jul 3. pii: btv405.

Forcefield_PTM – AMBER Forcefield Parameters for Post-translational Modifications

Forcefield_PTM

:: DESCRIPTION

Forcefield_PTM is a set of self-consistent AMBER forcefield parameters for frequently occurring post-translational modifications (PTMs).

::DEVELOPER

the Multi-scale Systems Engineering Laboratory (MSEL)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Forcefield_PTM: Ab Initio Charge and AMBER Forcefield Parameters for Frequently Occurring Post-Translational Modifications.
Khoury GA, Thompson JP, Smadbeck J, Kieslich CA, Floudas CA.
J Chem Theory Comput. 2013 Dec 10;9(12):5653-5674.

Forcefield_NCAA – AMBER Forcefield Parameters for Non-canonical Amino Acids

Forcefield_NCAA / FFNCAA

:: DESCRIPTION

Forcefield_NCAA is a set of self-consistent AMBER forcefield parameters for non-canonical amino acids. It allows you to design and derivatize peptides containing NCAAs for use as drugs.

::DEVELOPER

the Multi-scale Systems Engineering Laboratory (MSEL)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Forcefield_NCAA: ab initio charge parameters to aid in the discovery and design of therapeutic proteins and peptides with unnatural amino acids and their application to complement inhibitors of the compstatin family.
Khoury GA, Smadbeck J, Tamamis P, Vandris AC, Kieslich CA, Floudas CA.
ACS Synth Biol. 2014 Dec 19;3(12):855-69. doi: 10.1021/sb400168u.

mhsmm 0.4.16 – Parameter Estimation and Prediction for Hidden Markov and semi-Markov models for data with multiple Observation Sequences

mhsmm 0.4.16

:: DESCRIPTION

mhsmm is a software of parameter estimation and prediction for hidden Markov and semi-Markov models for data with multiple observation sequences. The software is suitable for equidistant time series data, with multivariate and/or missing data.

::DEVELOPER

Jared O’Connell and Jonathan Marchini.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R package

:: DOWNLOAD

  mhsmm

:: MORE INFORMATION

Citation

Jared O’Connell, Soren Hojsgaard (2011).
Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R.
Journal of Statistical Software, 39(4), 1-22.

REDEMPTION 20150708 – Reduced Dimension Ensemble Modeling and Parameter Estimation

REDEMPTION 20150601

:: DESCRIPTION

REDEMPTION is a MATLAB toolbox for the identification of parameters and parameter ensembles of ODE models from time-series data.

:: DEVELOPER

Chemical and Biological Systems Engineering Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / windows/ MacOsX
  • MatLab

:: DOWNLOAD

 REDEMPTION

:: MORE INFORMATION

Citation

REDEMPTION: Reduced Dimension Ensemble Modeling and Parameter Estimation.
Liu Y, Manesso E, Gunawan R.
Bioinformatics. 2015 Jun 14. pii: btv365.

GZ-gamma – Estimate Parameter of Substitution Rate Variation among Sites

GZ-gamma

:: DESCRIPTION

GZ-gamma is designed to estimate the expected number of substitutions of each amino acid (nucleotide) site, and the gamma shape parameter for the rate variation among sites, using a combination of ancestral sequence inference and maximum likelihood estimation when the phylogenetic relationships of these homologous sequences are known.

::DEVELOPER

Jianzhi Zhang ,  Xun Gu 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

  GZ-gamma

:: MORE INFORMATION

Citation:

Gu, X. and J. Zhang J (1997)
A simple method for estimating the parameter of substitution rate variation among sites.
Mol. Biol. Evol. 14:1106-1113