Principal Research Scientist
CurrentNeural Plasticity, Lognormal Networks, Mathematical Oncology, Memory and Autism, Symbolic Abstraction,
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@theoretical-biology.org
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Gabriele Scheler is listed as Computational Neuroscience and Theoretical Biology at Carl Correns Foundation for Mathematical Biology, a with 2 employees, based in San Francisco Bay Area, United States. AeroLeads shows a work email signal at theoretical-biology.org and a matched LinkedIn profile for Gabriele Scheler.
Gabriele Scheler previously worked as Principal Research Scientist at Carl Correns Foundation For Mathematical Biology and Co Founder at Carl Correns Foundation For Mathematical Biology. Gabriele Scheler holds Ph.D., Logic, Statistics And The Theory Of Science from Ludwig-Maximilians Universität München.
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My main focus is to build models of cellular computation, models of how the cell computes and exchanges information with its environment. Specifically, I develop a theory of memory based on synaptic, intrinsic, neuromodulatory-induced plasticity and intracellular processes in neurons. Cellular computation reaches beyond neuroscience into many other fields, such as cancer biology, cardiology, etc. I am also a co-founder of the Carl Correns Institute to work on the vision of mathematical modelling for the prevention and treatment of human disease.
Listed skills include Computational Biology, Bioinformatics, Algorithms, Systems Biology, and 18 others.
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Mountain View
Neural Plasticity, Lognormal Networks, Mathematical Oncology, Memory and Autism, Symbolic Abstraction,
Mountain View Ca
Started to research possibilities for doing a non-profit startup, outlining a vision, collecting initial funding pledges, and getting informed about support for non-profit organizations, strategic development, legal structure and other questions. Found colleagues which share the vision. Developed a website and a mission statement.
- Computational Neuroscience: Worked on the concept of general neural plasticity, based on ion channel and GPCR modulation. Applied the concept of intrinsic plasticity by parametrization of model neurons to show effects on large-scale neural networks. Investigated topological connectivity and synchronization. - Bioinformatics: Working with Yuan Yao, I also published on statistical graph analysis for metabolic and protein interaction networks. - Systems Biology: Developed a model for protein signal transduction collaborative with an experimental approach for the cAMP/PKA/PDE pathway (with Dill and Richter, Conti, UCSF).Contributed to collaborative grant proposal on dopamine receptor plasticity in addiction research in striatal medium spiny neurons with the Gallo Center at USCF (Bonci/Hopf).- BioClub: Organized a long-running seminar series on mathematical biology, the biological modeling club.
San Francisco Bay Area
Bioinformatics, Sequence Alignment, Perl/Python script access to databases, Running bioinformatics projects
Greater Boston Area
Investigated graph analysis tools with applications to biological databases (protein interaction) and neuronal networks.
Berkeley Ca
- Neural Networks: Developed the concept of fast synaptic switching, i.e. neural networks with alternate weight sets, with applications in technical domains (with J Schumann). - Neuroscience: Outlined and published a model and review of GPCR plasticity.
La Jolla Ca
- Computational neuroscience: Learned to apply computational modeling to electrophysiological recordings from rat brain slices, and developed a modified integrate-and-fire neuron model capable of representing variation in afterhyperpolarization. This model was applied to represent dopamine modulation of prefrontal cortex working memory by altered reverberation in the network and perceptual attention by adjusting tuning curves (with JM Fellous).- Extensive background research on neurons, brain areas, and biophysics.
Munich Area, Germany
- Neural Networks: Obtained a scholarship from the State of Bavaria for my work on computational linguistics. - Worked on grammar correction, text summarization, and lexical analysis (with Fischer, Aretoulaki, Brauer). Received a personal DFG grant for neural networks research (1996). Developed an event-based spiking neuron simulator (SPIKENET) (with Florian Wagner).
Martinsried Near Munich
- Bioinformatics: Worked on a protein sequence database, MIPS (later Biomax Informatics AG) and developed one of the first dedicated techniques for protein sequence comparison based on a novel algorithm for pattern classification, adaptive distance metrics.- Published an applications of ADM to phonology (=string comparison).
Heidelberg Area, Germany
- Computational Linguistics: Worked on problems in statistical lexical analysis, corpus linguistics and machine translation. Started a group on Neural Networks in computational linguistics. - Taught introductory classes in logic and linguistics. - Co-edited (with Wermter and Riloff) a book on Statistical Approaches in NLP (which appears in Webster's Timeline History of NLP 1929 - 2007.)
Munich Area, Germany
I learned to program in LISP and PROLOG and worked on my dissertation research in Natural Language Processing /Machine Translation/Q&A systems using a PROLOG-based knowledge engine.
Thesis: A PROLOG-based natural language interpretation program focusing on lexical semantic analysis
Fields of Interest: Language Typology, Montague Grammar, Logic, Psychology of Mind, Phonology
3 month stay. In the winter.
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Gabriele Scheler works for Carl Correns Foundation for Mathematical Biology.
Gabriele Scheler is listed as Computational Neuroscience and Theoretical Biology at Carl Correns Foundation for Mathematical Biology.
AeroLeads has found 1 work email signal at @theoretical-biology.org for Gabriele Scheler at Carl Correns Foundation for Mathematical Biology.
Gabriele Scheler is based in San Francisco Bay Area, United States while working with Carl Correns Foundation for Mathematical Biology.
Gabriele Scheler has worked for Carl Correns Foundation For Mathematical Biology, Stanford University, San Francisco State University, Northeastern University, and Uc Berkeley.
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Gabriele Scheler holds Ph.D., Logic, Statistics And The Theory Of Science from Ludwig-Maximilians Universität München.
Gabriele Scheler is listed with skills including Computational Biology, Bioinformatics, Algorithms, Systems Biology, Computer Science, Pattern Recognition, Machine Learning, and Neural Networks.
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