## D-MATRIX protocols

## D-MATRIX statistics

## D-MATRIX specifications

### Information

Unique identifier | OMICS_22247 |
---|---|

Name | D-MATRIX |

Interface | Web user interface |

Restrictions to use | None |

Input data | An orthologous or co-regulated genes upstream sequences. |

Programming languages | Other |

Computer skills | Basic |

Stability | No |

Maintained | No |

### Maintainer

**This tool is not available anymore.

## Publication for D-MATRIX

## D-MATRIX in pipeline

[…] from the kidney-liver homogenate, 400 μl of this solution was mixed with 600 μl solution gp (50 mm tris-hcl, 10 mm edta, 1% sds, 30 mm sodium acetate), then transferred to a tube containing 0.5 g **d** matrix beads (mp biomedicals, usa) and 650 μl acid phenol:chloroform (ambion life technologies, usa). the tubes were bead-beated in two intervals of 40 sec each in the cold (with a 2 min pause […]

## D-MATRIX in publications

(292)
[…] te κi of each optical mode i is defined as κi ≡ κ0,i + κa,i + κb,i, where κ0,i refers to the intrinsic optical loss rate of the mode, and κa,i, κb,i are the exchange losses to waveguides a and b. the **d-matrix** elements dji specify the coupling between input fields \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} […]

*library_books*

### An efficient approach for feature construction of high dimensional microarray data by random projections

[…] experimental design is shown in ., in random projection, if we have d-dimensional data originally then it is projected through the origin to a k-dimensional (k << d) subspace, using a random k***d matrix**, r, whose columns have unit lengths []. using matrix notation where xd*n is the original set of n d-dimensional observations, xk×nrp=rk×dxd×n(3), , gives the summary of parameters used. […]

[…] is the euclidean norm., let us consider a simulator (e.g. fc) which receives inputs in rm and returns outputs in rm (instead of r). then the gp emulator described in § would not work. let y be the m×**d matrix** with column j the jth run of the simulator. the dimension reduction in the output space can be described as follows: (i) subtract off the mean for each dimension m to obtain the centred […]

[…] \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$e_{2\omega ,i}' = d_{ij}e_{\omega ,j}'{ {\mathrm{voigt}}}$$\end{document}e2ω,i′=dijeω,j′voigt, where normalized shg **d matrix** for 4mm and mm2 symmetry is4\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \ […]

[…] {c}_{13}\\ {}{c}_{21}\kern0.75em {c}_{22}\kern1em {c}_{23}\\ {}{c}_{31}\kern0.75em {c}_{32}\kern0.75em {c}_{33}\end{array}\right] $$\end{document}pm=c11c12c13c21c22c23c31c32c33, where c11 is a d×**d matrix**, c12 is a d×l matrix, c13 is a d×m matrix, c21 is an l×d matrix, c22 is an l ×l matrix, c23 is an l×m matrix, c31 is an m×d matrix, c32 is an m×l matrix and c33 is an m ×m matrix. obviously, […]

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