Expertise: Bioinformatics
Tools: CWL, Genomics, Python, R, Transcriptomics, Jupyter notebook
Expertise: Traslational Research
Tools: PCR, Transcriptomics, Microarray analysis, Animal models
Remedios Otero Candelera began her research career with clinical work and has progressively participated in translational research projects until she became the leader of the Respiratory Diseases group of the Cardiovascular, Respiratory and other Systemic Pathology Area at the Institute of Biomedicine of Seville on the campus of the Virgen del RocĂo University Hospital. He also coordinates the research group of the Andalusian Plan for Research, Development and Innovation (PAIDI) (CTS551): Research ...
Expertise: Genomics, Metagenomics, NGS, Python, evolution
Tools: Genomics, Python, Snakemake, Transcriptomics
Expertise: Bioinformatics
Tools: R, Transcriptomics
Expertise: Bioinformatics, Genomics, Metagenomics, Data Management
Tools: CWL, Jupyter notebook, Nextflow, Molecular Biology, Workflows, Microbiology, Transcriptomics, Perl, Python, R
Expertise: Bioinformatics, Computer Science, Data Management, Genetics, Genomics, Machine Learning, Metagenomics, NGS, Scientific workflow developement, Software Engineering
Tools: Databases, Galaxy, Genomics, Jupyter notebook, Machine Learning, Nextflow, nf-core, PCR, Perl, Python, R, rtPCR, Snakemake, Transcriptomics, Virology, Web, Web services, Workflows
Dad, husband and PhD. Scientist, technologist and engineer. Bibliophile. Philomath. Passionate about science, medicine, research, computing and all things geeky!
Teams: MAB - ATGC
Organizations: Centre National de la Recherche Scientifique (CNRS)
https://orcid.org/0000-0003-3791-3973Expertise: Bioinformatics, Genomics, algorithm, Machine Learning, Metagenomics, NGS, Computer Science
Tools: Transcriptomics, Genomics, Python, C/C++, Web services, Workflows
Teams: Harkany Lab
Organizations: Medical University of Vienna
https://orcid.org/0000-0001-5920-2190Expertise: Systems Biology, Bioengineering, Bioinformatics, Neuroscience
Tools: Workflows, Machine Learning, Transcriptomics