A5005992798- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Machine Learning in Bioinformatics
- Biomedical Text Mining and Ontologies
- Digestive system and related health
- Single-cell and spatial transcriptomics
- Plant Molecular Biology Research
- Big Data and Business Intelligence
- Cancer-related molecular mechanisms research
- RNA and protein synthesis mechanisms
- Data Mining Algorithms and Applications
- Bacteriophages and microbial interactions
- RNA modifications and cancer
- Plant Pathogens and Fungal Diseases
- Plant and Fungal Interactions Research
- RNA Research and Splicing
- Entomopathogenic Microorganisms in Pest Control
- Plant Gene Expression Analysis
- Genomics and Phylogenetic Studies
- Mycorrhizal Fungi and Plant Interactions
Umeå Plant Science Centre
2024
Umeå University
2024
BASF (United States)
2022
Bordeaux Population Health
2017-2021
Université de Bordeaux
2017-2021
Inserm
2017-2020
Centre National de la Recherche Scientifique
2017-2020
Laboratoire Bordelais de Recherche en Informatique
2017-2020
Institut Polytechnique de Bordeaux
2018
Universidad de Murcia
2015
As the capacity for generating large-scale molecular profiling data continues to grow, ability extract meaningful biological knowledge from it remains a limitation. Here, we describe development of new fixed repertoire transcriptional modules, BloodGen3, that is designed serve as stable reusable framework analysis and interpretation blood transcriptome data. The construction this based on co-clustering patterns observed across sixteen immunological physiological states encompassing 985...
Abstract The revolution in new sequencing technologies is greatly leading to understandings of the relations between genotype and phenotype. To interpret analyze data that are grouped according a phenotype interest, methods based on statistical enrichment became standard biology. However, these synthesize biological information by priori selecting over-represented terms may suffer from focusing most studied genes represent limited coverage annotated within gene set. Semantic similarity...
Abstract Long non‐coding RNAs (lncRNAs) have emerged as important regulators of many biological processes, although their regulatory roles remain poorly characterized in woody plants, especially gymnosperms. A major challenge working with lncRNAs is to assign functional annotations, since they a low coding potential and cross‐species conservation. We utilised an existing RNA‐Sequencing resource performed short RNA sequencing somatic embryogenesis developmental stages Norway spruce ( Picea...
The possibility of validating biological macromolecules with locally disordered domains like RNA against solution properties is helpful to understand their function. In this work, we present a computational scheme for predicting global and mimicking the internal dynamics molecules in solution. A simple coarse-grained model one bead per nucleotide two types intra-molecular interactions (elastic excluded volume interactions) used represent chain. elastic are modeled by set Hooke springs that...
Motivation The recent revolution in new sequencing technologies, as a part of the continuous process adopting innovative protocols has strongly impacted interpretation relations between phenotype and genotype. Thus, understanding resulting gene sets become bottleneck that needs to be addressed. Automatic methods have been proposed facilitate sets. While statistical functional enrichment analyses are currently well known, they tend focus on well-known genes ignore information from...
The agricultural industry and regulatory organizations define strategies build tools products for plant protection against pests. To identify different plants their related pests avoid inconsistencies between such organizations, an agreed shared classification is necessary. In this regard, the European Mediterranean Plant Protection Organization (EPPO) has been working on defining maintaining a harmonized coding system (EPPO codes). EPPO codes are easy way of referring to specific organism...
Abstract The revolution in new sequencing technologies, by strongly improving the production of omics data, is greatly leading to understandings relations between genotype and phenotype. To interpret analyze these massive data that are grouped according a phenotype interest, methods based on statistical enrichment became standard biology. However, synthesize biological information priori selecting over-represented terms may suffer from focusing most studied genes represent limited coverage...
Nowadays, one of the main challenges in biology is to make use several sources data improve our understanding life. When analyzing experimental data, researchers aim at clustering genes that show a similar behavior through specific external conditions. Thus, functional interpretation crucial and involves making whole subset terms annotate these which can be relatively large redundant. The manual expertise clearly decipher functions may related gene set timeconsuming becomes impracticable...
Abstract As the capacity for generating large scale data continues to grow ability extract meaningful biological knowledge from it remains a limitation. Here we describe development of new fixed repertoire transcriptional modules. It is meant serve as stable reusable framework analysis and interpretation blood transcriptome profiling data. supported by customized resources, which include workflows, fingerprint grid plots visualizations, interactive web applications. These provide access vast...