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SVOLGIMENTO DEL CORSO INTEGRATO E MODALITÀ D ’ ESAME

A.A. 2013-201 4 CORSO INTEGRATO DI INFORMATICA E BIOINFORMATICA per il CLT in BIOLOGIA MOLECOLARE Scuola di Scienze, Università di Padova Docenti: Dr. Mauro Conti (Informatica) e Dr. Stefania Bortoluzzi (Bioinformatica). SVOLGIMENTO DEL CORSO INTEGRATO E MODALITÀ D ’ ESAME.

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SVOLGIMENTO DEL CORSO INTEGRATO E MODALITÀ D ’ ESAME

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  1. A.A. 2013-2014CORSO INTEGRATO DI INFORMATICA E BIOINFORMATICAper il CLT in BIOLOGIA MOLECOLAREScuola di Scienze, Università di PadovaDocenti: Dr. Mauro Conti (Informatica) e Dr. Stefania Bortoluzzi (Bioinformatica)

  2. SVOLGIMENTO DEL CORSO INTEGRATO E MODALITÀ D’ESAME • II semestre del I anno • Impegno didattico di 5 crediti: • 24 ore di lezione frontale • 32 ore di esercitazioni al computer • Così suddivise: • Valutazione finale (Idoneità): in base all’esito delle esercitazioni e di una verifica scritta individuale.

  3. WEB SITE DEDICATO AL CORSO http://compgen.bio.unipd.it/~stefania/Didattica/AA2013-2014/

  4. ORGANIZZAZIONE DEL CORSO INTEGRATO

  5. ORARIO E AULE ONLINE

  6. TESTI e materiali CONSIGLIATI • INFORMATICA • Colussi, File', Rossi, Informatica di base, Libreria progetto, 2003. • J. Glenn Brookshear (2006) Informatica: una panoramica generale. Pearson/Addison Wesley. (approfondimenti) • Python: http://www.python.it/doc/Howtothink/HowToThink_ITA.pdf • BIOINFORMATICA • Materiale lezioni • Risorse e tutorial online • Per approfondimento facoltativo: Fondamenti di Bioinformatica, Krane e Raymer, Pearson, 2007

  7. “Researchers need to be obliged to document and manage their data with as much professionalism as they devote to their experiments.” THE BIG DATA ERA •  Importance of data: • Retrieval • Integration • Analysis Nature journal Issue of 4 2008  An at least basic knowledge of bioinformatic methods in unavoidable also for experimental researchers  Bioinformatics from basic methods for managing biosequences to systems biology models

  8. With advances in technologies, investigators are increasinglygenerating and using large, complex, and diverse datasets. Consequently, the biomedicalresearchenterpriseisincreasinglybecoming data-intensive and data-driven. However, the ability of researchers to locate, analyze, and use Big Data (and more generallyallbiomedical and behavioral data) isoftenlimited for reasonsrelated to access to relevant software and tools, expertise, and otherfactors. D2K aims to develop the new approaches, standards, methods, tools, software, and competenciesthatwillenhance the use of biomedical Big Data by supportingresearch, implementation, and training in data science and otherrelevantfields. NIH BIG DATA to Knowledge (BD2K)

  9. Importance of Bioinformatics Deep sequencing data analysis

  10. DATABASES AND DATA RETRIEVAL Biosequences and Gene-related info

  11. WORKING WITH BIOSEQUENCES Alignments and similarity search

  12. gene details comparisons Annotation Tracks SNPs NAVIGATING GENOMES By Genome Browsers official sequence

  13. EXAMPLES FROM MORE ADVANCED BIOINFORMATICS Gene expression and RNA-seq data analysis

  14. Opportunities and Challenges •  OPPORTUNITIES: • estimate the odds of your future childrenbeingborn with somethinglike Down syndrome • securepaternity test • customizedcancer-fightingdrugs • personalized medicine

  15. Opportunities and Challenges •  OPPORTUNITIES: • estimate the odds of your future childrenbeingborn with somethinglike Down syndrome • securepaternity test • customizedcancer-fightingdrugs • personalized medicine “When your bank account or credit card is compromised, the situation is painful but recoverable. You can close the account, wipe the slate clean and start over. You cannot change or revoke your DNA once it’s leaked,” says Gene Tsudik – UCI – GenoDroid project. •  CHALLENGES: • do you have something more “private” than your DNA? • consumers fear losing insurance coverage if results are shared, companies don’t want to reveal proprietary information about customized treatments

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