TALK KEYWORD INDEX
This page contains an index consisting of author-provided keywords.
| 1 | |
| 1H-NMR | |
| 2 | |
| 2D NMR | |
| 3 | |
| 3D chromatin network | |
| 3D genomics | |
| 3D RNA | |
| A | |
| Adaptive Sampling | |
| Adipogenic Stromal Cells | |
| Affinity Propagation clustering | |
| Aggregation | |
| Aggressive subclones | |
| aging | |
| agro-ecology | |
| AI | |
| algorithm | |
| aLhr2 | |
| AlphaFold | |
| Alternative Splicing | |
| Amino-acid sequences | |
| Analysis Pipeline | |
| Anchor compound | |
| Angiogenesis | |
| Annotation | |
| anonymity | |
| Antimicrobial resistance | |
| Archaea | |
| artificial microbial consortia | |
| assembly | |
| association genetics | |
| Assortativity | |
| atypical segment detection | |
| Automated analysis | |
| automatic integration | |
| automating | |
| AVITI | |
| B | |
| bacterial evolution | |
| Bacterial genome assembly | |
| Bacterial phylogeny | |
| Bacterial secretion systems | |
| Bagging models | |
| beehive products | |
| Benchmark | |
| benchmark comparison | |
| Benchmarking | |
| binary tree | |
| Binding site | |
| Bio-ontologies | |
| bioactive compounds | |
| Bioinformatic | |
| Bioinformatic software | |
| Bioinformatics | |
| bioinformatics analyses | |
| bioinformatics tools | |
| Biological Graphs | |
| Biological networks | |
| Biologie des Systèmes | |
| Biomarkers | |
| Biomaterials | |
| BIOTIC | |
| biotic interactions | |
| Bipolar disorder | |
| bitmap | |
| Bone marrow | |
| Boolean model | |
| Boolean models for biological systems | |
| Breast cancer | |
| bulk RNAseq | |
| BurkinaBioinfo | |
| C | |
| C.elegans | |
| C/D box small nucleolar RNA (SNORD) | |
| Cancer | |
| cancer genomics | |
| Carbohydrate | |
| Causal analysis | |
| Causal inference | |
| CAZy Database | |
| cellular senescence | |
| Challenges | |
| changepoint detection | |
| Chemoinformatics | |
| Chimeras | |
| ChIP-seq | |
| Chromatin | |
| Chromatin contacts | |
| Chromosomes | |
| Chronic lymphocytic leukemia | |
| CI/CD | |
| circRNA | |
| Classification | |
| Classifier | |
| climate change | |
| Clonal heterogeneity | |
| Cloud | |
| cloud computing | |
| CNN | |
| CNV | |
| Co-expression | |
| Coding DNA | |
| cohort study | |
| Collagen interaction | |
| Collimonas | |
| Colorectal | |
| community | |
| comparative analyses | |
| Comparative genomics | |
| computational benchmark | |
| Computational biology | |
| Compétences | |
| Confounding effect | |
| confounding variables | |
| Consensus network | |
| consensus OPLS-DA | |
| constraint-based modelling | |
| Copy number variations | |
| Crop resilience | |
| Cross-sample Contamination | |
| Cytometry | |
| D | |
| dada2 | |
| dark matter | |
| Data base | |
| data challenge | |
| Data Engineering | |
| data fusion | |
| data integration | |
| Data Integration and Visualization | |
| Data lake | |
| data management | |
| data reduction | |
| data science | |
| data visualization | |
| Data-Leakage | |
| Database | |
| dataset integration | |
| de novo gene birth | |
| deconvolution | |
| Deconvolution algorithms | |
| Deep Learning | |
| Deep-learning | |
| DeepOmics | |
| Degraded DNA | |
| detection | |
| DevOps | |
| diagnostic | |
| Differential analysis | |
| Differential expression | |
| differential expression analysis | |
| Differentially methylated regions (DMRs) | |
| Dimension Reduction | |
| dinoflagellates | |
| Distance | |
| distributed computing | |
| distributed infrastructure | |
| DMP | |
| DNA methylation | |
| DNA repair | |
| DNBSEQ-T7 | |
| Docker | |
| Drosophila | |
| Drosophila model organism | |
| drug repurposing | |
| Drug-Repurposing | |
| Drug-target identification | |
| Drug-target interactions (DTIs) | |
| E | |
| Early detection | |
| ecological model | |
| embedding learning | |
| Endometriosis | |
| enhancers | |
| Enrichment analysis | |
| ensemble clustering | |
| EnviBIS | |
| Environmental biorefinery | |
| environmental biotechnology processes | |
| environmental DNA | |
| Enzyme | |
| Epidemiologic surveillance | |
| epigenetic | |
| epigenetics | |
| Epitranscriptomic | |
| eQTL | |
| eQTL hotspots | |
| Erythropoiesis | |
| eukaryotes | |
| EuroScienceGateway | |
| evolution | |
| Evolutionary Biology | |
| Exome sequencing | |
| expression | |
| expression quantitative trait loci | |
| Expression regulation | |
| extrinsic variability | |
| F | |
| factor models | |
| FAIR | |
| fair comparison | |
| FAIR data | |
| FAIR data analysis | |
| FAIR principles | |
| FAIR science | |
| fba | |
| Feature extraction | |
| Feature selection | |
| Federation | |
| fermented vegetables | |
| Ferments | |
| Fiber | |
| Fibronectin | |
| Forest soil | |
| Formation | |
| freshwater cyanobacteria | |
| Fruit development | |
| Fruits | |
| function prediction | |
| Functional and taxonomic annotation | |
| functional annotation | |
| functional differentials | |
| Functional diversity | |
| functional motifs | |
| Fungal guilds | |
| Fungi | |
| G | |
| Galaxy | |
| GEA | |
| Gene annotations | |
| Gene duplication | |
| Gene evolutionary ages | |
| gene expression | |
| Gene family | |
| gene regulation | |
| Gene Regulatory Network | |
| Gene regulatory networks | |
| Gene Regulatory Networks (GRN) | |
| gene-regulatory network | |
| genetic disorders | |
| Genetic Diversity | |
| Genetic hitchhiking | |
| Genetic imputation | |
| Genome | |
| Genome annotation | |
| genome assembly | |
| Genome browser | |
| Genome browsers | |
| genome evolution | |
| Genome function | |
| genome portals | |
| Genome regulation | |
| Genome repeats | |
| genome sampling | |
| genome sequencing | |
| genome stability | |
| Genome structure | |
| genome-scale metabolic networks | |
| Genomes | |
| genomic adaptation | |
| Genomic predictions | |
| Genomic Rearrangements | |
| genomic variation | |
| genomic variations | |
| Genomics | |
| Genomics core facility | |
| genotype-phenotype relationship | |
| genotypes | |
| Genotyping | |
| GitHub | |
| Gold standard corpus | |
| graph | |
| Graph neural network | |
| Graph Neural Networks | |
| Graph pangenomes | |
| Graph Representation Learning | |
| graph theory | |
| Graph-embedding | |
| graphe de connaissance sémantique | |
| Graphical User Interface | |
| Graphs | |
| GRO-seq | |
| GSEA | |
| GWAS | |
| GxE interactions | |
| Génomique Environnementale | |
| H | |
| H3K27ac | |
| H3K27me3 | |
| H3K9me3 | |
| Habitat | |
| Haplotig purging | |
| Haplotype | |
| Haplotypes | |
| heat | |
| Heterogenous data | |
| Hi-C | |
| Hi-C data | |
| HiC | |
| hierarchical clustering | |
| High pathogenic avian influenza viruses | |
| High-dimension | |
| high-throughput sequencing data | |
| HLAtyping | |
| Holobiont | |
| homologous recombination | |
| homology | |
| homology search | |
| horizontal gene transfer | |
| Horizontal transfers | |
| Host-pathogen interactions | |
| HPC cluster | |
| HPC infrastructure | |
| human disease | |
| Human gut microbiome | |
| human gut microbiota | |
| Human Phenotype Ontology (HPO) | |
| Hybridization-Capture | |
| I | |
| Image analysis | |
| Image-based segmentation | |
| imaging | |
| Immunity | |
| Immuno-oncology | |
| Immunoevasion | |
| immunology | |
| Immunotherapy | |
| impact environnemental | |
| In silico predictions | |
| Incomplete data | |
| Information system | |
| Infrastructure | |
| insertions | |
| interactive training | |
| INTERCHANGE | |
| Interoperability | |
| interpretability | |
| intégration de données | |
| Intra-species diversity | |
| Intégration de connaissances | |
| Isoform analysis | |
| ISRU | |
| K | |
| k-mers | |
| keynote | |
| Kinase Superfamily | |
| Kink-Turn family | |
| Knockoffs | |
| Knowledge database | |
| Knowledge Discovery | |
| Knowledge Graph | |
| Knowledge-Graph | |
| knowledgebase | |
| Kronecker Optimized METhod | |
| Kubernetes | |
| L | |
| Labos 1point5 | |
| Large alphabet de Bruijn graph | |
| large language model | |
| Large-scale computational modeling | |
| Large-sized benchmark dataset | |
| Latent space | |
| LIME Algorithm | |
| LIMS | |
| Lindley | |
| Lindley-CUSUM process | |
| Linked Data | |
| local score | |
| Long reads | |
| Long-read | |
| Long-read assembly | |
| long-read nanopore sequencing | |
| Long-read sequencing | |
| Long-Read Sequencing facility | |
| Longevity | |
| Loss-of-function variants | |
| low pathogenic avian influenza viruses | |
| LSM-8 | |
| LTR-retrotransposons | |
| Lung cancer | |
| Lung radiotherapy | |
| Lymph node | |
| M | |
| Machine learning | |
| Machine-Learning | |
| Mapping | |
| MAPS | |
| marine organisms | |
| Markov CLustering algorithm | |
| Mash | |
| mass spectrometry | |
| Master | |
| Mathematical modeling | |
| Matrix factorization | |
| maximal exact matches | |
| Mechanisms of Disease | |
| Mediation | |
| Medical imaging | |
| MES | |
| meta-analysis | |
| meta-assembly | |
| Metabarcode | |
| Metabolic fluxes | |
| metabolic modelling | |
| Metabolic Models | |
| metabolic network | |
| Metabolic networks | |
| Metabolic networks reconstruction | |
| metabolism | |
| Metabolomic analysis | |
| Metabolomics | |
| MetaCyc pathways | |
| Metagenome | |
| Metagenomic | |
| Metagenomics | |
| metaomics data | |
| Metaplastic breast cancer | |
| metataxonomic study | |
| Metatranscriptomics | |
| Metric | |
| microbial association network | |
| microbial communities | |
| microbial community | |
| Microbial genomics | |
| microbial guilds | |
| Microbial Translocation | |
| microbiology | |
| Microbiome | |
| microbiome data | |
| microbiota | |
| Microbiote intestinal | |
| microprotein | |
| Microservice | |
| Microsporidia | |
| Migration | |
| Milk | |
| Minimal databases | |
| Minimizers | |
| MinION | |
| miRNA | |
| misconceptions | |
| mitochondria | |
| mitochondrial diseases | |
| Mobile genetic elements | |
| Modelisation | |
| Modelling | |
| Modélisation | |
| mole-rat | |
| molecular clock | |
| Molecular docking | |
| molecular dynamics | |
| Molecular dynamics simulations | |
| molecular mimicry | |
| Mosaic | |
| Mosaic integration | |
| multi-basic cleavage site | |
| Multi-omics | |
| multi-omics analysis | |
| multi-omics data integration | |
| multi-omics integration | |
| multi-proteins similarity | |
| multi-way comparison | |
| multiblock | |
| multimodal analysis | |
| Multiple interactions | |
| Multiple myeloma | |
| multiple testing | |
| Multivariate analysis | |
| Musa | |
| mutation rate | |
| Myriapods | |
| N | |
| Nanopore | |
| Natural language processing | |
| ncRNA targets | |
| Neighborhood metrics | |
| Nematodes | |
| neopeptides | |
| Network | |
| network analysis | |
| network inference | |
| Network modeling | |
| Networks | |
| Neuroblastoma | |
| New Generation Sequencing (NGS) | |
| next-generation sequencing | |
| Nextflow | |
| NGS | |
| NMF | |
| Non-assembled genomes | |
| non-coding DNA | |
| non-coding transcription | |
| non-laboratory models | |
| Non-model organisms | |
| nonsense suppression therapies | |
| nonsense variations | |
| Nutrition | |
| O | |
| Oligosaccharide diversity | |
| Olive Quick Decline Syndrome | |
| Omic | |
| Omics | |
| Omics analysis | |
| omics data | |
| Omics Data Integration | |
| oncologie | |
| Oncology | |
| One Health | |
| ONT | |
| ontologies | |
| Ontology | |
| Open access | |
| open genomic resources | |
| Open Science | |
| Open-Science | |
| opioid | |
| Organic matter degradation | |
| orphan genes | |
| Orthology | |
| Ovarian cancer | |
| Oxalobacteraceae | |
| Oxford Nanopore Sequencing | |
| Oxford Nanopore Technologies | |
| P | |
| paleogenomics | |
| Paleontology | |
| Paleoproteomics | |
| Pan-genomics | |
| Pangenome | |
| Pangenome graph | |
| Pangenome graphs | |
| pangenome praph | |
| Pangenomics | |
| Parameterized Complexity | |
| Parasites | |
| pathway analysis | |
| Patient classification | |
| PCHi-C | |
| PDAC | |
| Pea Genome | |
| performance analysis | |
| Personalized medicine | |
| Pharmaceutical industry | |
| Phasing | |
| Phenotypes | |
| phenotypic adaptations | |
| Phylogenetic Analysis | |
| Phylogenetic datation | |
| phylogenomic | |
| phylogenomics | |
| Pig | |
| Pinot Noir | |
| pipeline | |
| pipelines | |
| Plant genetic diversity | |
| plant parasitic nematodes | |
| Platform | |
| polymerase | |
| Population genetics | |
| population genomics | |
| population polymorphism | |
| Pore-C analysis | |
| Post-transcriptional modifications | |
| precision medicine | |
| Prediction | |
| Preprocessing | |
| privacy | |
| Protein Binding | |
| Protein Diversification | |
| protein folds | |
| Protein interaction | |
| Protein Language Model | |
| protein language models | |
| protein mutation | |
| Protein Protein Interaction | |
| Protein structure | |
| Protein structure prediction | |
| protein-protein interaction network | |
| Proteogenomic | |
| proteomics | |
| Provence | |
| proximal optimization | |
| Pseudo-labeling | |
| pseudogenes | |
| Pseudogymnoascus destructans | |
| Psoriasis | |
| Psychosis | |
| PU-learning | |
| Pulsar | |
| Pédagogie | |
| Q | |
| QTL detection | |
| Quality control | |
| R | |
| R library | |
| R package development | |
| R shiny | |
| R. Thomas’ discrete modeling framework | |
| Radio-toxicity | |
| Random Forest | |
| Ranking | |
| Rare disease | |
| Rare diseases | |
| Rare Variants | |
| Recombination | |
| Reconstruction | |
| reference genome | |
| Regeneration | |
| Regenerative medicine | |
| Regulatory DNA sequence | |
| Regulatory elements | |
| Regulatory genomics | |
| Regulatory Sequence | |
| Regulatory variants | |
| RELIEFF | |
| remote homologs identification | |
| Repeated-sequences | |
| Representation Learning | |
| representative genomes | |
| Reproducibility | |
| Reproducible science | |
| RGCCA | |
| Rhabdoid tumors | |
| Rheumatoid Arthritis synovial macrophages | |
| RiboMethSeq | |
| ribonucleases | |
| ribosomal RNA epitranscriptomics | |
| Rice | |
| RNA 3D structure | |
| RNA half-life | |
| RNA maturation | |
| RNA-end sequencing | |
| RNA-RNA interactions | |
| RNA-seq | |
| RNA-Seq data analysis | |
| RNAseq | |
| Rshiny | |
| RStudio | |
| RuleFit | |
| ruminants | |
| réseau de laboratoire | |
| S | |
| Schizophrenia | |
| Science popularization | |
| scientific competition | |
| Scientific competition | |
| scNaUmi-seq | |
| Scoring function | |
| scRNA-seq | |
| Segmentation | |
| Semantic Web | |
| Semi supervised learning | |
| Semi-supervised learning | |
| sequence analysis | |
| Sequence similarity networks | |
| Sequence to graph mapping | |
| service | |
| sex-differences | |
| Shiny | |
| Short reads | |
| shotgun metagenomics | |
| Silencers | |
| simulation framework | |
| Simulations | |
| Single cell RNA sequencing | |
| Single Cell RNA-seq | |
| Single Cell RNASeq | |
| single-cell | |
| Single-cell RNA-seq | |
| Single-cell RNAseq | |
| Ski2-like helicases | |
| smoking | |
| Snakemake | |
| snakemake pipelines | |
| Snoussi’s constraints | |
| software | |
| Solution space sampling | |
| sORF | |
| space biomining | |
| Spatial | |
| spatial biology | |
| Spatial transcriptomic | |
| Spatial transcriptomics | |
| species | |
| Squidpy | |
| Standardization | |
| statistical significance | |
| Statistics | |
| Strobemers | |
| Structural annotation | |
| structural variation | |
| Structure evaluation | |
| Sufficient dimension reduction | |
| supervised learning | |
| Supervised machine learning | |
| survival analysis | |
| synapomorphy | |
| sysadmin | |
| Systems Bioinformatics | |
| systems biology | |
| T | |
| T lymphocytes | |
| Targeted metagenomics | |
| Taxonomic annotation | |
| taxonomic classification | |
| Taxonomic profiling | |
| TCGA | |
| Technologies comparison | |
| Telomeres | |
| Tissue engineering | |
| Toxicogenomic | |
| Toxicology | |
| Toxins | |
| Trajectory Inference | |
| Transcript-based segmentation | |
| Transcription factors | |
| Transcription factors binding | |
| Transcription start site | |
| Transcriptional Regulatory Networks | |
| Transcriptomic | |
| Transcriptomics | |
| Transfer learning | |
| transformer | |
| Transition matrix | |
| Translation speed profiling | |
| tree of life | |
| Tumor classification | |
| Tumor microenvironment | |
| Ty | |
| type 2 diabetes | |
| U | |
| UI / UX | |
| Ultra-high-risk patients | |
| Unix | |
| Uveal melanoma | |
| V | |
| V3-V4 size | |
| Variable selection | |
| Variant calling | |
| variant prioritization | |
| Variation graph | |
| Viral hepatitis | |
| Viruses | |
| Visium | |
| Visualisation | |
| visualization | |
| W | |
| WASM | |
| web application | |
| Web applications | |
| Web components | |
| Web platform | |
| webtool | |
| WGS analysis | |
| Whole exome sequencing | |
| Whole Genome Sequencing | |
| Wine authenticity | |
| Workflow | |
| Workflow developments | |
| Workflow Manager | |
| workflows | |
| Workshop | |
| Y | |
| Yeast | |
| Z | |
| ZooMS | |
| é | |
| écologie | |
