Remembrance of Experiments Past: Analyzing Time Course Datasets to Discover Complex Temporal Invariants

Abstract

Current microarray data analysis techniques draw the biologist's attention to targeted sets of genes but do not otherwise present global and dynamic perspectives (e.g., invariants) inferred collectively over a dataset. Such perspectives are important in order to obtain a process-level understanding of the underlying cellular machinery, especially how cells react, respond, and recover from stresses.

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Document Details

Document Type
Technical Report
Publication Date
Feb 02, 2005
Accession Number
AD1020288

Entities

People

  • Bhubaneswar Mishra
  • Deept Kumar
  • Marco Antoniotti
  • Marina Spivak
  • Naren Ramakrishnan

Organizations

  • Courant Institute of Mathematical Sciences, NYU

Tags

DTIC Thesaurus Topics

  • Attachment
  • Cells
  • Chromosome Structures
  • Cohesion
  • Cytoskeleton
  • Data Analysis
  • Genetic Phenomena
  • Genetic Structures

Fields of Study

  • Biology

Readers

  • Educational Psychology
  • Molecular and genetic basis of cancer.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML