User:Boris/Temp/APB
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- Hardware
- High Performance Computing (... at the bench: GPUs, FPGAs, Clusters)
- Cloud computing
- Tools
- Unix (installation notes, commands, principles, pipe)
- Unix system administration (and security)
- Unix automation shellscripts, cron
- Unix wget
- Network Configuration
- Apache (serving a local file)
- MySQL (introduction, installation, MariaDB)
- Tools for the bioinformatics lab (APB, CLUSTAL, EMBOSS, PHYLIP, T-Coffee, HMMER)
- GBrowse (installation notes, viewing annotations, LDAS installation notes, LDAS usage)
- Programming
- IDE (Integrated Development Environment) (Komodo)
- Regular Expressions
- Screenscraping
- Perl (installation notes, CPAN, principles, syntax, one liners)
- Perl basic programming
- Perl hash example
- Perl LWP example
- Perl MySQL example
- Perl MySQL introduction (DBI Mac OSX installation notes)
- Perl OBO parser
- Perl programming
- Perl programming exercises 1
- Perl programming exercises 2
- Perl programming Data Structures
- Perl references
- Perl simulation
- Perl retrieve fasta
- Perl/MySQL example
- Perl: Object oriented programming
- Perl: Ugly programming
- Perl: Using forms
- BioPerl (installation notes, programming, BP run, BP ext, tutorials)
- PHP
- BioPython (scope, highlights, installation, use, support)
- Graphical output (PNG and SVG)
- Autonomous agents
- Algorithms
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- Algorithms on Sequences
- Dynamic Programming (Dynamic Programming and Optimal Pairwise Sequence Alignment, appropriate problems for DP, procedural and recursive formulation of solutions)
- Multiple Sequence Alignment
- Genome Assembly (long and short reads)
- Algorithms on Structures
- Docking
- Protein Structure Prediction (ab initio)
- Algorithms on Trees
- Computing with trees (Bayesian approaches for phylogenetic trees, tree comparison)
- Algorithms on Networks
- Network metrics (Degree distributions, Centrality metrics, other metrics on topology, small-world- vs. random-geometric controversy)
- Communication and collaboration
- MediaWiki
- Web Communication
- HTML essentials
- HTML 5
- SADI Semantic Automated Discovery and Integration
- CGI (introduction, configuring apache, executing a script, query string input)
- Statistics
- Pattern discovery
- Correlation (Covariance matrices and their interpretation, application to large problems, collaborative filtering, MIC and MINE)
- Clustering methods (Algorithms and choice (including: hierarchical, model-based and partition clustering, graphical methods (MCL), flow based methods (RRW) and spectral methods). Implementation in R if possible)
- Cluster metrics (Cluster quality metrics (Akaike, BIC)–when and how)
- The Map Equation (A network flow approach to hierarchical partitioning of large datasets)
- Machine learning (Classification problems: Neural Networks, HMMs, SVM..)
- R
- R plotting
- R programming (Scope, passing parameters, scalars, matrices, lists, functions)
- R EDA
- R regression (linear and non-linear, Calculation, confidence limits and interpretation)
- R PCA
- R Clustering
- R Classification (Phrasing inquiry as a classification problem, dealing with noisy data, machine learning approaches to classification, implementation in R)
- R hypothesis testing (Major approaches and when to apply them (including simulation methods for arbitrary PDFs))
- Bioconductor (Scope, contents, highlights use)
- Applications
- Data integration (BioMart: Biodata integration, and data-mining of complex, related, descriptive data)
- Text mining (Use cases, tasks and metrics, taggers, vocabulary mapping, Practicals: R-support, Python/Perl support, others...)
- High-throughput sequencing
- Functional annotation (GFF)
- Microarray analysis (... in R: differential expression and multiple testing; Loading and normalizing data, calculating differential expression, LOWESS, the question of significance, FWERs: Bonferroni and FDR; SAM and LIMMA)
