جست‌وجوی استاد و پژوهشگر

Thomas Walterمشاهده پروفایل

استاد

• Biomedical Image Analysis
• Machine Learning
• Computational Pathology
• +۴ مورد دیگر

Thomas Walter is a Professor at Mines ParisTech and Director of the Centre for Computational Biology (CBIO) , a research group affiliated with the Institut Curie and INSERM . His work focuses on applying Machine Learning and Computer Vision to biomedical image analysis, particularly in high-content screening and computational pathology . He also serves as Deputy Director of the Computational Oncology (U1331) unit and leads the Statistical Learning and Modeling of Biological Systems team. PhD in Medical Image Analysis (2003, Mines ParisTech) Postdoctoral work at EMBL (European Molecular Biology Laboratory) Director of CBIO since 2018 Holder of a PRAIRIE Chair (Paris Artificial Intelligence Research Institute) since 2019 Dr. Walter's research bridges biomedical imaging , machine learning , and cancer genomics . Key areas include: Statistical reconstruction of biological networks Prediction of tumor progression at genomic/transcriptomic levels Development of deep learning methods for cell cycle analysis Integration of multi-omics data for precision oncology Tools for spatial transcriptomics (e.g., autoFISH, RNA2seg) Recent publications highlight his work in spatial transcriptomics , immunotherapy outcome prediction , and deep learning for digital pathology . His team has developed open-source tools like FISH-quant and pyHiM for single-molecule RNA imaging analysis. Scientific Honors: PRAIRIE Chair (2019) for AI research in life sciences Dr. Walter actively contributes to teaching deep learning for image analysis in multiple graduate programs across France, including courses at Mines ParisTech , Université Paris-Saclay , and Institut Curie . His software tools (FISH-quant, pyHiM) and methodological frameworks (e.g., Cut-Detector, PointFISH) have become standard resources in bioimage informatics.

Fabien Duveauمشاهده پروفایل

پژوهشگر

• Evolutionary Biology
• Genetics
• Molecular Biology
• +۵ مورد دیگر

Fabien Duveau is a CNRS Researcher at the Laboratory of Biology and Modelling of the Cell (LBMC) at École Normale Supérieure de Lyon. He leads the eGRIDE project, funded by an ERC Consolidator Grant, investigating evolutionary mechanisms of gene regulation in dynamic environments. His work focuses on understanding how gene expression plasticity and mutational effects shape organismal adaptation. Duveau holds a PhD from Université Paris 7/CNRS (2011), followed by postdoctoral research at the University of Michigan and Université Paris 7. He joined LBMC in 2019 as part of Gaël Yvert’s team, supported by an ANR Young Researchers grant. His research integrates experimental and computational approaches, including high-throughput RNA sequencing and genetic mapping in yeast ( Saccharomyces cerevisiae ), to study how regulatory evolution balances mutational randomness and environmental selection pressures. Key areas include gene expression noise, cis/trans regulatory variation, and fitness outcomes under environmental stress. Recognitions include the prestigious ERC Consolidator Grant (2024), awarded for innovative projects advancing fundamental biological understanding. Duveau collaborates across disciplines, combining evolutionary genetics with systems biology to predict regulatory evolution in natural and pathological contexts.

Louis Lambrechtsمشاهده پروفایل

پژوهشگر

• Arbovirus transmission
• Insect-virus interactions
• Mosquito genetics
• +۱۲ مورد دیگر

Louis Lambrechts is a Researcher and Head of the Insect Infection & Immunity Group at the Institut Pasteur in Paris, France, within the Department of Virology. His research focuses on the ecology, evolution, and genetics of mosquito-virus interactions, particularly involving Aedes aegypti and arboviruses such as dengue and Zika. He leads a dynamic research team and multiple national and international projects funded by agencies including ANR and EU consortia. His research interests include arbovirus transmission dynamics, vectorial capacity, mosquito genetics, evolutionary ecology, host-pathogen interactions, and the role of microbiota in vector competence. He employs genomics, quantitative genetics, and experimental evolution to understand the mechanisms underlying variation in mosquito susceptibility to viral infection. His work has important implications for predicting and controlling arboviral disease outbreaks. Lambrecht’s recent publications reveal key insights into the genetic and environmental factors influencing arbovirus transmission, including the role of mosquito population variation in Zika transmission in Africa, the impact of endogenous viral elements, and the discovery of antiviral roles for cytochrome P450 enzymes. His research integrates molecular biology, field studies, and computational modelling, contributing to a comprehensive understanding of vector-borne disease systems. He has mentored numerous PhD students, postdoctoral researchers, and visiting scientists, fostering a collaborative and interdisciplinary research environment. His lab collaborates widely with institutions across Europe, Africa, and the Americas. Lambrecht’s work is supported by multiple ongoing projects such as CAZIKANO, INTRANZIGEANT, ANR PILGRIM, and LIPOARBO-IVI, focusing on Zika virus transmission, genetic drivers of vectorial capacity, and mosquito-virus specificity. His lab is also involved in broader initiatives like the LabEx IBEID and the Emerging Infectious Diseases program at Institut Pasteur.

Camille Berthelotمشاهده پروفایل

پژوهشگر

• Comparative Functional Genomics
• Evolutionary Genomics
• Gene Regulation
• +۱۲ مورد دیگر

Camille Berthelot is a Principal Investigator and head of the Comparative Functional Genomics research group at the Institut Pasteur in Paris, France. Her work lies at the intersection of evolutionary biology, genomics, and reproductive physiology, with a focus on understanding how genomic changes drive evolutionary innovations in vertebrates, particularly the evolution of menstruation in primates. Her research leverages cutting-edge technologies including single-cell RNA sequencing, organoid models, and computational frameworks to compare gene expression and regulation across species such as humans, macaques, and mice. She investigates how evolutionary changes in gene function contribute to novel traits and how these relate to diseases like endometriosis. A major focus is the use of menstrual fluid as a non-invasive biomarker source for endometriosis, a direction highlighted in her systematic review published in Reproductive Biology and Endocrinology . Her recent publications span high-impact journals such as Science , Genome Research , and Nature Ecology & Evolution , covering topics from teleost fish phylogeny to regulatory evolution in mole-rats. These works reveal a consistent trend in using comparative genomics to decode deep evolutionary questions, often in collaboration with institutions like QMUL and INSERM. ERC Starting Grant (EVOMENS) – Decoding the genetics of menstruation evolution in primates Collaborative project on hypoxia adaptation in mole-rats Development of bioinformatics tools like FINSURF for non-coding variant classification She actively mentors a team of postdocs, PhD students, and master’s interns, including Claire Lavergne, Leo Zeitler, and Eulalie Liorzou. Former members such as Malgorzata Gazda and Axelle Brulport have gone on to independent academic positions, reflecting her role in training next-generation scientists. Camille Berthelot returned from maternity leave in June 2024 and remains actively engaged in research, publication, and team leadership at the Institut Pasteur.

Thomas Cokelaerمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Data Analysis
• Machine Learning
• +۱۲ مورد دیگر

Thomas Cokelaer is a researcher at the Institut Pasteur, affiliated with the Bioinformatics and Biostatistics HUB and based at the Platform Biomics. Since October 2018, he has led the SALSA (dry-lab) group, focusing on bioinformatics software development and data analysis. His interdisciplinary background spans astronomy, plant modeling, systems biology, and drug discovery. Institution: Institut Pasteur Unit: Bioinformatics and Biostatistics HUB Platform: Platform Biomics Group: SALSA (dry-lab group) leader His research interests center on bioinformatics, next-generation sequencing (NGS) analysis, machine learning, data visualization, and reproducible research. He develops and maintains several widely used open-source tools including Sequana (NGS pipelines), BioServices (biological web services), Bioconvert (format conversion), Sequanix (GUI for Snakemake), and GDSCTools (pharmacogenomics). He is deeply committed to promoting reproducibility in computational research through initiatives like reprohackathons. The recent publications reflect a strong trend in computational biology, with a focus on developing bioinformatics methodologies, improving data analysis workflows, and applying these tools to diverse biological problems such as fungal pathogenesis, cancer pharmacogenomics, mitochondrial metabolism, and viral evolution. The work spans genomics, transcriptomics, systems biology, and software engineering. He has contributed to numerous scientific software projects as Principal Investigator, including Sequana, Bioconvert, GDSCTools, DREAMTools, and Sequanix. He has also taught courses in scientific programming with Python and reproducible data analysis at the Institut Pasteur. His collaborative network includes researchers from EMBL-EBI, Sanger Institute, INRIA, and international partners within the Pasteur Network. The SALSA group hosts master’s students and visiting researchers annually.

• R-loop Biology
• Epigenetics
• DNA Methylation
• +۴ مورد دیگر

Frédéric Chédin is a Professor in the Department of Molecular and Cellular Biology at the University of California Davis, College of Biological Sciences. He has held continuous faculty positions at UC Davis since 2004, progressing from Assistant Professor (2004-2010) to Associate Professor (2010-2015), and currently serving as full Professor (2015-present). His research focuses on R-loop biology, DNA methylation, and epigenetic regulation. Chédin's laboratory investigates how RNA:DNA hybrids form, persist, and impact genome stability, with particular emphasis on their roles in transcription, chromatin organization, and disease mechanisms. His work has established foundational methodologies for R-loop detection and mapping, including critical assessments of common techniques like the S9.6 antibody. Chédin's publication record demonstrates consistent leadership in R-loop research, with numerous high-impact papers in journals like PNAS , Nature Communications , and Molecular Cell . His recent work explores protein-mediated R-loop stabilization, R-loop classification systems, and connections between R-loops and topological stress management. Director of NIH T32 Predoctoral Training Program in MCB (2020-present) Co-Director of NIH T32 Program (2019-2020) Chair of Integrative Genetics and Genomics (2015-2019) His laboratory trains numerous graduate students and postdoctoral researchers, with frequent collaborators including Stella Hartono and Lionel Sanz appearing as first authors on key publications. Chédin maintains active service roles in graduate education and program leadership at UC Davis.

• Epigenetics
• Chromatin Biology
• Developmental Biology
• +۴ مورد دیگر

Nathalie Dostatni is a Professor at Sorbonne University and Research Team Leader at the Curie Institute, affiliated with the Core Dynamics (UMR3664) research unit. She has held senior research positions since 2012, focusing on epigenetic mechanisms that govern cell identity during embryonic development and their implications in cancer biology. Epigenetic plasticity and polarity of the embryo Chromatin dynamics in development Transcriptional regulation by morphogen gradients Genome integrity in germ stem cells Her recent work combines interdisciplinary approaches (genetics, biophysics, and quantitative imaging) to dissect the role of chromatin assembly factors like CAF-1 in heterochromatin formation and the transcriptional precision of morphogens like Bicoid in Drosophila embryos. Publications highlight her contributions to understanding stochastic transcriptional dynamics, sharp gene expression borders, and chromatin-mediated genome stability. Collaborations include biophysicists (M. Coppey at Institut Curie/UMR168, C. Fradin at McMaster University) and theoreticians (A. Walczak at ENS, Paris). Her lab investigates chromatin dynamics in two key contexts: (1) CAF-1's role in meiotic cells and germ stem cells, and (2) Bicoid morphogen gradient interpretation in transcriptional precision. The team utilizes Drosophila as a model organism for genetic and imaging studies.

• Computer Science
• Parallel Computing
• Dynamic Programming
• +۳ مورد دیگر

Jerry Lacmou Zeutouo is a Lecturer in the field of Networks and Data at Université de Picardie Jules Verne (UPJV), contributing to computer science research through advanced algorithm development and optimization. His work primarily focuses on parallel computing, dynamic programming, and computational biology. Academic Rank: Lecturer at UPJV Institution: Université de Picardie Jules Verne Research Interests: Dr. Zeutouo specializes in designing and optimizing parallel algorithms for dynamic programming and database security. His research spans: Coarse-Grained Multicomputer (CGM) architectures K-anonymity in distributed databases RNA folding and bioinformatics applications Longest Common Subsequence (LCS) constraints Publication Trends: His work emphasizes solving computational bottlenecks via parallelism, particularly in cloud environments, bioinformatics, and database security. Key themes include: Transformer-based models for cold start mitigation in FaaS Multicomputer algorithms for dynamic programming Four-splitting and Four-Russians techniques for optimization

Odile Sismeiroمشاهده پروفایل

پژوهشگر

• Transcriptomics
• Next-Generation Sequencing (NGS)
• Microbial Genetics
• +۳ مورد دیگر

Odile Sismeiro is a Senior Research Engineer at the Transcriptome and Epigenome Platform within the Biomics Pole at the Institut Pasteur . With over three decades of experience, she has been pivotal in advancing RNA sequencing technologies since 2009. Diplôme Universitaire de Technologie Diplôme d’Études Scientifiques et Techniques from CNAM, Paris Her research intertwines Transcriptomics , Microbial Genetics , and Host-Pathogen Interactions , particularly through developing and applying: DNA array technology Next-Generation Sequencing (NGS) RNA-seq data analysis pipelines Key publication themes highlight: Streptococcus pathogenicity networks RNA-based immune sensing mechanisms Vector-borne disease genetics Microbial biofilm regulation She actively contributes to: Scientific training programs Technological development projects Collaborative research across multiple Institut Pasteur units

• Bioinformatics
• Machine Learning
• Neural Networks
• +۵ مورد دیگر

Ole Winther is a Professor at the Department of Biology , University of Copenhagen , and a Professor at the Section for Cognitive Systems , DTU Compute , Technical University of Denmark . He specializes in high-dimensional biological data analysis, machine learning, and data science. Academic Affiliations: University of Copenhagen (Computational and RNA Biology), DTU Compute (Cognitive Systems) Leadership Roles: Chief Research Officer at raffle.ai, CTO at FindZebra, Head of ELLIS Unit Copenhagen, co-PI of Machine Learning for Life Science (MLLS) Center Research Interests Bioinformatics: Protein sequence analysis (SignalP, DeepLoc, DeepTMHMM), single-cell gene expression, RNA/DNA level regulation Latent Variable Models: Variational autoencoders, diffusion models, deep generative models, structured mean-field, matrix factorization Natural Language Processing: Enterprise search applications, medical context LLMs, joint retrieval/generation models AI for Science: Surrogate models for physical models (density functional theory), fast scientific dataset generation Publication Trends His research focuses on deep learning methods for bioinformatics and AI applications, with a strong emphasis on variational inference, generative models, and probabilistic architectures. Publications span top venues like Bioinformatics , NeurIPS , ICML , and JMLR , addressing both theoretical and applied challenges. Teaching He teaches courses on deep learning at both institutions ( 02456 Deep Learning at DTU and NDAK24002U Deep Learning at University of Copenhagen). Research Group His current group includes PhD/postdoc researchers like Panagiotis Antoniadis, Felix G. Teufel, and Irene R. Rodriguez. Former advisees include Casper Kaae Sønderby, Marco Fraccaro, and Lars Maaløe, many of whom now hold prominent industry/academic positions.

Shinnosuke SEKIمشاهده پروفایل

استادیار

• Algorithmic Self-Assembly
• Molecular Programming
• Theoretical Computer Science
• +۳ مورد دیگر

Shinnosuke SEKI is an Assistant Professor at the University of Electro-Communications in Chofu, Tokyo, Japan. He was affiliated as a visiting researcher at Université de Lyon from 2019 to 2021. His research focuses on exploring the programmability of biomolecules like DNA and RNA using the Oritatami model, an algorithmic framework simulating co-transcriptional folding processes. This work aims to develop paradigms and languages enabling biomolecules to execute arbitrary computations. Research Interests: SEKI’s work bridges computer science and molecular biology, emphasizing algorithmic approaches to biomolecular systems. His projects investigate how self-assembly processes can be harnessed for computational purposes, with applications in synthetic biology and nanotechnology. No specific articles, awards, or grants are listed in the provided text.

Jessica Valle Oreroمشاهده پروفایل

استادیار

• Biophysics
• Structural Biology
• DNA Dynamics
• +۳ مورد دیگر

Jessica Valle Orero is an Assistant Professor at the American University of Paris (AUP) in the Department of Computer Science, Mathematics, and Environmental Science. She obtained her PhD in 2012 from the École Normale Supérieure de Lyon, followed by postdoctoral research at Columbia University and the École Normale Supérieure in Paris. Her research focuses on the physics of biomolecules, particularly DNA and protein dynamics, employing advanced techniques like neutron scattering and single-molecule magnetic tweezers. She has taught courses at institutions including Columbia University and AUP since 2022. Education: MSci Physics (UCL, 2008), PhD Physics (ENS Lyon/ILL, 2012) Postdoctoral experience: Fernandez Lab, Columbia University (2013–2017); Biophysics Lab, ENS Paris (2018–2022) Research interests include DNA fiber dynamics, protein folding mechanics, and the interplay between molecular and macroscopic scales. Her work bridges experimental and theoretical approaches, with contributions to understanding DNA glass transitions and mechanical protein aging. Current research is conducted at ENS Paris, focusing on biophysical mechanisms of biomolecular systems. Teaching spans applied statistics, environmental science, and foundational math courses at AUP. Over 30 peer-reviewed publications highlight her expertise in single-molecule biophysics and structural biology.

Seki Shinnosukeمشاهده پروفایل

دانشیار

• Molecular Computation
• Theoretical Computational Models
• RNA Computing Systems
• +۳ مورد دیگر

Seki Shinnosuke is an Associate Professor at the Department of Computer and Network Engineering at the University of Electro-Communications in Tokyo. He serves as a Visiting Professor at the Laboratoire de l'Informatique du Parallélisme (LIP) in France from 2024-2026, focusing on collaborative research in molecular computation. His academic journey includes a bachelor's and master's in engineering from the University of Electro-Communications, followed by a doctorate in computer science from the University of Western Ontario, Canada, and postdoctoral work in Canada and Finland. His research centers on molecular computation, particularly RNA-based systems and the Oritatami model. Collaborations with CNRS have advanced RNA computing and scalable molecular programs. Key contributions include theoretical models and experimental in-vitro implementations for molecular engineering. Publications highlight advancements in RNA co-transcriptional folding, programmable single-stranded architectures, and DNA computing fundamentals. His work bridges computer science and molecular biology, addressing challenges in bio-inspired computing and algorithmic nanotechnology.

Etienne Kornobisمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Evolutionary Biology
• Transcriptomics
• +۸ مورد دیگر

Etienne Kornobis is a bioinformatician and researcher at the Institut Pasteur , affiliated with the Bioinformatics and Biostatistics Hub . He obtained his PhD in Biology from the University of Reykjavik in 2011 and has held postdoctoral positions in Spain before joining the Institut Pasteur in 2016. He became a member of the Bioinformatics and Biostatistics Hub in 2018, where he continues his work on transcriptomics and bioinformatics methodology. His research interests include bioinformatics, evolutionary biology, transcriptomics, population genetics, RNA splicing, genome analysis, reproducible research, workflow development, long-read sequencing, alternative splicing, and microbial genomics . His work emphasizes computational methods for analyzing complex biological data, particularly in non-model organisms and microbial systems. The recent publications of Etienne Kornobis span a broad range of topics in genomics and molecular biology, with a strong trend toward transcriptomic analysis, host-pathogen interactions, microbial genomics, and methodological development in bioinformatics . His work frequently involves high-throughput sequencing, alternative splicing, and data reproducibility, reflecting his expertise in computational biology and systems-level analysis. Scientific Awards: No awards mentioned in the provided text. Etienne Kornobis is actively involved in research mentoring and collaborative projects. He leads the Bioconda project and contributes to Bioconvert , both critical tools for bioinformatics software distribution and data format conversion. He has also taught courses on reproducible data analysis and Software Carpentry , indicating a strong commitment to training and open science. There is no mention of formal student advising or grant leadership in the text provided. Labs and Teams: Bioinformatics and Biostatistics Hub (current) Revive Consortium (past) Epigenetic Regulation unit (past) Expertise group: SysBio – Systems Bioinformatics (past) Biomics – Dry-Lab (past)

Natalia Pietrosemoliمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Biostatistics
• Genomics
• +۶ مورد دیگر

Natalia Pietrosemoli is a Senior Bioinformatician at the Center for Bioinformatics, Biostatistics and Integrative Biology (C3BI) at Institut Pasteur in Paris, where she has been working since November 2015. She specializes in functional and pathway analysis at the genomic level, with expertise in integrative analysis of different omics data both at large-scale and for small datasets. Her work focuses on decreasing the complexity of biological systems by grouping genes and proteins into the pathways they are involved in to increase comprehension of these systems. Her research interests span bioinformatics, biostatistics, genomics, transcriptomics, systems biology, functional genomics, pathway analysis, and omics data integration. She has developed several bioinformatics tools including g-RITA (Gene Set Enrichment Analysis visualization), Sherpa (Transcriptomic Analysis tool), and coGSEA (Comparative Gene Set Enrichment Analysis tool). Her recent publications (2023-2025) demonstrate expertise in viral pathogenesis (particularly Lassa virus and SARS-CoV-2), bacterial biofilms (Leptospira), immunology, and bioinformatics methodology development. She actively participates in teaching and training programs, including the Bioinformatics program for PhD students at Institut Pasteur and the PHINDaccess courses in Comparative Genomics and Functional OMICs. She has collaborated on numerous interdisciplinary research projects, often working with experimental colleagues to provide bioinformatics support and insights. PhD in Computational Biology from Rice University's School of Bioengineering Postdoctoral fellowship at the Swiss Institute of Bioinformatics' Bioinformatics Core Facility Visiting scholar positions at the National Centre for Biotechnology (CNB-CSIC) and Spanish National Cancer Centre Master's degree in Modeling and Simulation of Complex Realities from ICTP and SISSA Dr. Pietrosemoli leads the PHINDaccess twinning initiative with the Institut Pasteur de Tunis and serves as Principal Investigator for several software development projects including g-RITA, Sherpa, and coGSEA. Her work bridges computational analysis with experimental biology, providing critical insights into complex biological systems through sophisticated bioinformatics approaches.