A.A. 2014-2015 CORSO INTEGRATO DI INFORMATICA E BIOINFORMATICA per il CLT in BIOLOGIA MOLECOLARE Scuola di Scienze, Università di Padova Docenti: Proff.

Presentazione sul tema: "A.A. 2014-2015 CORSO INTEGRATO DI INFORMATICA E BIOINFORMATICA per il CLT in BIOLOGIA MOLECOLARE Scuola di Scienze, Università di Padova Docenti: Proff."— Transcript della presentazione:

1 A.A CORSO INTEGRATO DI INFORMATICA E BIOINFORMATICA per il CLT in BIOLOGIA MOLECOLARE Scuola di Scienze, Università di Padova Docenti: Proff. Roberto di Pietro (Informatica) 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. Insegnamento Lezione Esercitazione INFORMATICA 16 BIOINFORMATICA 8

3 WEB SITE DEDICATO AL CORSO

4 ORGANIZZAZIONE DEL CORSO INTEGRATO
LABORATORIO PRATICO BIOINFORMATICA LABORATORIO PRATICO INFORMATICA TEORIA INFORMATICA INTRODUZIONE ALLA BIOINFORMATICA 16 ore L 16 ore F 8 ore F

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: BIOINFORMATICA Materiale lezioni Risorse e tutorial online Per approfondimento facoltativo: Fondamenti di Bioinformatica, Krane e Raymer, Pearson, 2007

7 Nature journal Issue of 4 2008
THE BIG DATA ERA “Researchers need to be obliged to document and manage their data with as much professionalism as they devote to their experiments.”  Importance of data: Retrieval Integration Analysis Nature journal Issue of  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 NIH BIG DATA to Knowledge (BD2K)
With advances in technologies, investigators are increasingly generating and using large, complex, and diverse datasets. Consequently, the biomedical research enterprise is increasingly becoming data-intensive and data-driven. However, the ability of researchers to locate, analyze, and use Big Data (and more generally all biomedical and behavioral data) is often limited for reasons related to access to relevant software and tools, expertise, and other factors. D2K aims to develop the new approaches, standards, methods, tools, software, and competencies that will enhance the use of biomedical Big Data by supporting research, implementation, and training in data science and other relevant fields.

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 NAVIGATING GENOMES By Genome Browsers gene details comparisons
official sequence comparisons Annotation Tracks SNPs On the previous slide I diagrammed the UCSC Genome Browser representation of the genome and the annotation data—briefly I wanted to show you a sample of the kind of data we will examine as it actually looks in the Genome Viewer. Here you see a portion of the genome viewer, with the base positions—the official genome sequence--the top, and the many layers of data—annotation tracks--organized in that region. From any of this data if you click the features, you will be presented with even more detail about the items you see. The detail pages themselves link out to more resources, too. Shown here are some examples of Gene Details, cross-species alignment data, and SNPs. So much data, so well organized, is right at your fingertips now, thanks to the UCSC Genome Bioinformatics Group team.

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

14 Opportunities and Challenges
estimate the odds of your future children being born with something like Down syndrome secure paternity test customized cancer-fighting drugs personalized medicine

15 Opportunities and Challenges
estimate the odds of your future children being born with a genetic disease secure paternity test customized cancer-fighting drugs 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

16 BioMol- Informatica e Bioinformatica - Modulo di Informatica
Il modulo di Informatica si suddivide in lezioni di teoria (16 ore) e lezioni pratiche in lab. (16 ore). Il modulo si propone di fornire un’introduzione* su: architettura degli elaboratori; circuiti logici; rappresentazione dell'informazione; sistemi operativi; reti di calcolatori; Data Base, sicurezza --- cenni - programmazione (python). Roberto Di Pietro *il programma di dettaglio verrà discusso durante la prima lezione e messo on-line. Contatto: Ricevimento: Per eventuali ricevimenti contattatemi via ; indicativamente mercoledì pomeriggio, in studio, – fine