Algorithmic and Combinatorial Foundations of Pattern Discovery

Lecture slides:

• Monotony and Surprise Algorithmic and Combinatorial Foundations of Pattern Discovery
• http://www.cc.gatech.edu/~axa/papers A) Speciali
• http://www.cc.gatech.edu/~axa/papers B) Introductory Material
• Acknowledgements Gill Bejerano
• Form \x3D Function
• TITLE
• Bioinformatics the Road Ahead
• At a joint EU \x2D US panel meeting
• Which Information Anyway
• King Phillip Came Over For Green Soup
• The “Chinese” Taxonomy
• Summary
• Defining ‘’Class’’
• Class by Intension
• Statistical Classification
• Statistical Classification
• Statistical Classification
• Inferring Grammars
• Regular, Anomalous, Entropy, Negentropy
• Random, Regular, Compressible
• Random, Regular, Compressible
• Form \x3D Function
• Summary
• Privileging Syntactic Regularities in Strings
• Unavoidable Regularities
• Avoidable Regularities
• Periods cannot coexist too long
• Avoidable Regularities
• Squares or Tandem Repeats
• Detecting Squares
• Tandem Repeats, Repeated Episodes
• Pattern Discovery in WAKA
• Discovering instances of poetic allusion from anthologies of classical Japanese poems
• Cheating by Schoolteachers (the longest substring common to k of n strings)
• Summary
• General Form of Pattern Discovery
• Data Compression by Textual Substitution
• Consumer Prediction (Data Mining) Intrusion Detection (Security) Protein Classification (Bio\x2DInformatics)
• Of Exactitude in Science

Author: Alberto Apostolico, University Of Padova