'Fit model' diaporamas de présentation

Normalisation and Analysis of the Affymetrix Data

Normalisation and Analysis of the Affymetrix Data. David J Craigon. What I am not going to talk about. General microarray topics Biology. The introduction. Affymetrix workflow. Biological sample of some sort. Extract mRNA. Amplify. Label and Fragment. Analyse down to one number per gene.

775 views • 51 slides

Molecular Replacement

Molecular Replacement Martyn Winn CCP4 group, Daresbury Laboratory, UK What do we know from the diffraction data? The point group of the new crystal form, the volume of the asymmetric unit and hence the likely number of molecules it contains (Matthews coefficient).

1.26k views • 48 slides

Extreme Value Analysis

Extreme Value Analysis. FISH 558 Decision Analysis in Natural Resource Management 12/4/2013 Noble Hendrix QEDA Consulting LLC Affiliate Faculty UW SAFS. Lecture Overview. Motivating examples of extreme events Generalized Extreme Value Statistical Development

1.32k views • 48 slides

Critical Systems Validation

Critical Systems Validation. Objectives. To explain how system reliability can be measured and how reliability growth models can be used for reliability prediction To describe safety arguments and how these are used To discuss the problems of safety assurance

888 views • 45 slides

Robust Statistics Why do we use the norms we do?

754 views • 38 slides

Jacob L Strunk Jacob.Strunk@oregonstate.edu Nov 15, 2013

501 views • 36 slides

Lecture 18

Lecture 18. Stellar populations. Stellar clusters. S imple stellar populations: stars were probably all born at nearly the same time; thus have the same age and composition. Open clusters: contain 10-1000 stars loose structure. Globular clusters: 1000 - 1 million stars

500 views • 33 slides

Cetmap Atlantic update

405 views • 32 slides

Stat 112: Lecture 15 Notes

Stat 112: Lecture 15 Notes. Finish Chapter 6: Review on Checking Assumptions (Section 6.4-6.6) Outliers and Influential Points (Section 6.7) Homework 4 is due this Thursday. Please let me know of any ideas you want to discuss for the final project. .

383 views • 28 slides

Enzymes General

447 views • 28 slides

Class 7: Thurs., Sep. 30

Class 7: Thurs., Sep. 30. Outliers and Influential Observations. Outlier: Any really unusual observation. Outlier in the X direction (called high leverage point): Has the potential to influence the regression line.

376 views • 24 slides

Technology as the arm from school to home

258 views • 20 slides

Exclusive Production at HERA

346 views • 20 slides

Starter

336 views • 18 slides

Comparison of FT-IR with Wet Chemical Reference Methods

Comparison of FT-IR with Wet Chemical Reference Methods. Dr. Marc Coleman National Physical Laboratory. Contents. Description of measurements performed at a fibreglass manufacturing plant Comparison of HCl readings made by FT-IR and wet reference methods

392 views • 17 slides

Warm Up - Regression Review

Warm Up - Regression Review. The table below shows the value of rice produced in Texas from 2001 to 2007. a. Use a calculator to find the best fit model. Let x = the number of years since 2000. b. Using your model, predict the value of rice in Texas in 2015.

233 views • 14 slides

Enzymes A review of how they work

265 views • 13 slides

Explaining Statistical Models through Metadata

127 views • 12 slides

NEW EVOLUTIONARY MODELS OF HII GALAXIES

254 views • 12 slides

Enzymes

Enzymes. Important protein complexes. Background. Activation Energy: the energy needed to start non-spontaneous chemical reactions Catalyst: a compound that decreases activation energy and speeds the reaction. Catalysts are not consumed in the reaction so they are reuseable. Enzymes.

288 views • 12 slides