David’s team investigates how genetic alterations contribute to cancer development and the genetic wiring of cancer cells using approaches such as CRISPR genome editing. This provides fundamental insights into how cancers develop and evolve and how genetic changes in cancer genomes may be used as targets for cancer therapy. David’s expertise is in high-throughput functional genetic screens in human cells and mice, cancer genetics and computational biology.
Ludmil is an enthusiastic early career scientist with an interdisciplinary training and a strong computational background. His interests lie in leveraging the information hidden in large-scale omics data for better understanding of the mutational processes causing human cancer, for identifying potential cancer prevention strategies, and for developing novel approaches for targeted cancer treatment.
Dr Corpas is an experienced researcher, trainer and scientific communications strategist. Since 2017 he is founder and Chief Scientific Officer of Cambridge Precision Medicine Ltd, a company whose main objetive is to help clinicians make more accurate diagnoses. Among his current activities, he is the exclusive international organising partner of the Longevity World Forum and the director of the first Precision Medicine Online Course in Spanish. In addition, he also teaches intensive courses in Precision Medicine in London and New York twice a year and chairs the Precision Medicine Track at the BioData World West in San Francisco, California. His upcoming projects include the editorial of a topic on personal genomics in the Frontiers in Genetics journal and the organisation of the Personal Genome Conference at the Wellcome Campus Conference Centre. Dr Corpas is a prolific author and speaker, currently with 51 authored scientific publications and the acclaimed "Perfect DNA" book, a speculative futuristic novel exploring the ethical and social implications of personal genetic testing in society,
Dr. Dudoit's research and teaching activities concern the development and application of statistical methods and software for the analysis of biomedical and genomic data.
Her methodological research interests regard high-dimensional inference and include exploratory data analysis (EDA), visualization, loss-based estimation with cross-validation (e.g., density estimation, regression, model selection), and multiple hypothesis testing.
Much of her methodological work is motivated by statistical inference questions arising in biological research and, in particular, the design and analysis of high-throughput microarray and sequencing gene expression experiments, e.g., single-cell transcriptome sequencing (RNA-Seq) for discovering novel cell types and for the study of stem cell differentiation. My contributions include: exploratory data analysis, normalization and expression quantitation, differential expression analysis, class discovery, prediction, cell lineage inference, integration of biological annotation metadata (e.g., Gene Ontology (GO) annotation).
She am also interested in statistical computing and, in particular, reproducible research. She is a founding core developer of the Bioconductor Project (http://www.bioconductor.org), an open-source and open-development software project for the analysis of biomedical and genomic data.
Dr. Fernández Valverde is a researcher specializing in genomics and bioinformatics. Her main academic interest is to contribute to understanding the mechanisms involved in the immense phenotypic diversity present in the animal and plant kingdom. She is particularly interested in the role that non-conding RNAs play in the evolution of regulatory landscapes within the same and between different species
The recent explosion in genomic information facilitated by the invention of mass sequencing has revealed a large number of regulatory molecules including a large number of non-coding RNAs - arn molecules with zero or little protein coding potential. Many of these RNAs have important functions as modulators of genetic expression. In her group they study the evolutionary dynamics of non-coding RNA molecules using a variety of plant and animal species with various evolutionary scales. They use bioinformatics tools and genomic data to understand the evolution of these molecules and the regulatory mechanisms in which they participate
The Laboratory of Computational Genomics develops and uses computational methods to analyze genome and transcriptome sequence data and gene expression data to gain biological insights into an organism and make predictions about molecular processes. Under current funding, they are pursuing the assembly and annotation of two model organism genomes: medicinal leech, Hirudo medicinalis; and a Tardigrades species, H. dujardinii. Our approach integrates three data sources: high throughput genome and transcriptome sequencing and high-throughput peptide mass-spectrometry.
The Computational Biology Group is a young research team. One of their primary interests is to contribute to a better understanding of the epigenetic control of transcription. To do this, we are developing methods for the analysis of big and multidimensional biological data sets. Our work is highly collaborative and we are and have been a member of several high-profile national and international consortia such as the International Cancer Genome Consortium (ICGC) or the BLUEPRINT Consortium.
The focus of the Lab of Computational consequences is on the study, prediction, and evolution of genetic functional networks. The main data used is the sequence databases containing complete and draft genomes, as well as metagenomes (DNA sequences from random samples of a given environment). One of our main goals is the prediction and understanding of the functions of the vast amount of uncharacterized genes.
Dr. Nowick performed her doctoral work at the Max-Planck-Institute for Evolutionary Anthropology in Dr. Svante Pääbo’s lab on transcriptome evolution in primates and the functional characterization of FOXP2. She joint Dr. Lisa Stubbs lab at the Lawrence Livermore National Laboratory for her postdoctoral work in 2006 to study the evolution of zinc finger transcription factors in primates. The lab relocated in 2008 to the University of Illinois at Urbana-Champaign. In 2010 Dr. Nowick returned to Germany, to join the department of Dr. Hans Lehrach at the Max-Planck-Institute for Molecular Genetics in Berlin, where she worked on the analysis of RUNX1 target genes and allelic differences in human ZNF genes. She received an Advanced Postdoc award from the Volkswagen Foundation that supports her research group at the University Leipzig. She is an editor for the journal Molecular Biology and Evolution (MBE).
Diego obtained his Ph.D. from the University of California, Los Angeles in 2016 under the cotutorship of John Novembre and Kirk Lohmueller. His graduate research was focused on how demographic history impacts the genetic variation of alleles under natural selection using genomic information from canines and humans. Following his PhD studies, he did a Postdoc with Montgomery Slatkin, where he developed new methods to analyze past population history using genomic data from ancient and present-day samples. At LIIGH, he aims to leverage large-scale genomic datasets in order to develop statistical methods to infer the past history of various species and to understand how natural selection changes patterns of genetic and haplotypic variation.
Dr. Sankoff is a long-time member of the Centre de recherches mathématiques and former professor at the Université de Montréal. He is a Fellow of the Royal Society of Canada and of the International Society for Computational Biology and is active in the Canadian Institute for Advanced Research. He is a medalist of the Association francophone pour le savoir, recipient of the first Senior Scientist Accomplishment Award by the International Society for Computational Biology and the Weldon Memorial Prize and Medal from Oxford University. He is also a recipient of the Award for Exellence in Research from University of Ottawa. In 2013 the conference MAGE (Models and Algorithms for Genome Evolution) honoured Dr. Sankoff's 50th anniversary of research contribution. Dr. Sankoff was founding editor of Language Variation and Change (Cambridge) and serves on the editorial boards of a number of bioinformatics, computational biology and linguistics journals. In 2014 he received a honorary Doctoral degree from Tel Aviv University for contribution to computational biology.
Dr Thomas-Chollier's projects often involve predictions of binding regions for transcription factors (motif detection, de-novo motif discovery, ChIP-seq, ChIP-exo) and I am co-leader of RSAT.
She also has a strong interest for the evo-devo field, in particular the evolution of Hox and ParaHox protein sequences accross metazoans.
She analyzes next-generation sequencing data. Programs to analyze these data are changing in parallel with the fast improvements of sequencing technologies, making the work of a bioinformatician very dynamic! On a technical level, she is interested by the approaches for single-cell analyses and the technology of Web services.
The research focus of the Laboratory of Bioinformatics and Applied Genomics is the study of genome evolution and its phenotypic consequences in organisms of biotechnological interest using integrative strategies with a strong emphasis on bioinformatics and experimental validation tools. The Laboratory of Biocomputing and Applied Genomics continuously develops research projects in the areas of genomics of prokaryotes and eukaryotes, identification of biomarkers, applied statistical genetics, proteomic and metabolic profiles in different areas of biotechnological relevance, including aquaculture, agriculture, bio-mining, among other. Current research capabilities have also been exploited to establish new relationships with environmental and health agencies, national universities and international institutions.