Loading...
The MAB team (Methods and Algorithms for Bioinformatics) proposes mathematical and algorithmic methods (text and tree algorithms, combinatorial algorithms and optimization, probabilistic modeling, statistical machine learning) to address biological issues such as evolution, phylogeny, comparative genomics, functional annotation of genes and proteins, malaria, HIV, cancer. The software systems developed by MAB are available through the ATGC platform.
Open Access Files
80 %
Number of full texts
502
Number of records
173
Publishers' policy on open archives
Mapping of collaborations
Tags
Phylogeography
Data structures
DNA
Gene expression
Greedy
Phylogeny
Graph
Analyse
Bayesian inference
RNA-seq
Supertree
Complexity
Stringology
Construction algorithms
Compatibility
Complexité
Alignement
ChIP-seq
Bioinformatics
Autocorrelation
Accuracy
Algorithms
Dynamic programming
Coleoptera
RNA
Tool
Transcriptome
Border
Genome evolution
Transcriptomics
Cancer
Overlap
Period
Approximation
Assembly
Computer simulations
Duplication
Comparative genomics
Recombination
Arabidopsis thaliana
Software
Phylogenetic inference
Evolution
Species tree
Periodicity
Computational biology
Phylogenetic trees
Genomics
VNTR
Trees
Algorithm
Index
Phylogenomics
Automata
Data structure
Bioinformatique
Gene tree
Superstring
Pattern matching
Suffix array
Tandem repeats
Tandem repeat
Plasmodium falciparum
Génomique comparative
Consensus
Next Generation Sequencers
Alignment
Deep sequencing
Sequence analysis
NGS
K-mer
Indexing
Contracted de Bruijn graph
Malaria
HMM
MCMC
Next Generation Sequencing
Genome
Reads
Machine learning
Overlap graph
Sequence comparison
Parsimony
Approximation algorithm
Combinatorics
Phylogenetic
Motif
Phylogenetics
Maximum likelihood
Reconciliation
Algorithmique
Indexation
Distance methods
Sequence alignment
Scalability
Dynamic update
Suffix tree
Bayes
Molecular evolution
Least-squares