SimCluster: pat SimCluster: pat attern recognition attern - - PowerPoint PPT Presentation

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SimCluster: pat SimCluster: pat attern recognition attern - - PowerPoint PPT Presentation

Oct 06, 2023 159 likes •531 views

Universidade de So Paulo Departamento de Computao o e Matemtica LabPIB - Laboratrio de Processa cessamento de Informao Biolgica Prof. Dr. Vncio rvencio@usp.br SimCluster: pat SimCluster: pat attern recognition attern

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Universidade de São Paulo Departamento de Computação LabPIB - Laboratório de Processa

  • Prof. Dr. Vêncio

rvencio@usp.br

SimCluster: pat SimCluster: pat for composition

  • e Matemática

cessamento de Informação Biológica

attern recognition attern recognition nal data

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Pattern recognition What do we mean by Pattern Recogn gnition ?

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Pattern recognition

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Pattern recognition

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Pattern recognition

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Pattern recognition

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Biological motivation

Joyce & Palsson, Nat Rev Mol Cell Biol 2006

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Biological motivation

Joyce & Palsson, Nat Rev Mol Cell Biol 2006

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Technological tool to be used: quantit titative sequencing

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Technological tool to be used: quantit titative sequencing

http://www.genome.gov/sequencingcosts/

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Next-gen sequencing

Nature Reviews Genetics, 2009

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The technical problem we are addres

Wang et al., Nature Reviews Genetics, 2009

ssing

9

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2003

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Model – the urn model

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2004

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2007

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Crucial element in clustering analysis is: distance between objects

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Pattern recognition

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Model

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Crucial element in clustering analysis is: distance between objects

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Metric properties

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Additional “good” properties for comp positional analysis

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Additional “good” properties for comp positional analysis

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Additional “good” properties for comp positional analysis

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Aitchisonean Distance

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Aitchisonean Distance

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2007

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Model validation: simulated sequencin cing data from Affymetrix data

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Model validation: simulated sequencin cing data from Affymetrix data

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Model validation: simulated sequencin

  • mouse macrophages RNA
  • stimulated by different Toll-like rec

LPS, PIC, CPG, R848 and PAM

  • time-course: 0, 20, 40, 60, 80 and 1
  • Gilchrist M, et al.

Systems biology approaches ident negative regulator of Toll-like recep Nature 2006, 441:173–178.

  • Innate Immunity Systems Biology

http://www.innateimmunity-system

  • transcript abundances proportiona
  • simulated sampling using real-data

cing data from Affymetrix data

ceptor agonists: 120 minutes. ntify ATF3 as a eptor 4. msbiology.org al to Affy signal ta structure

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Model validation: simulated sequencin cing data from Affymetrix data

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Model validation: other examples (“cir circumstantial” evidence)

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Web site freely available for all

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Opportunities: there is more in Pattern rn Recognition beyond clustering

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Opportunities: there is more in Pattern rn Recognition beyond clustering

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Opportunities: there is more in Pattern rn Recognition beyond clustering

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Acknowledgements

  • Prof. Carlinhos

IME-USP e BIOINFO-USP Pro FM-

  • f. Edson Amaro Jr.
  • USP e HIAE