What is he best known for?
The fields of study he is best known for:
His main research concerns Cell biology, Neuroscience, Neurodegeneration, Mutant and Programmed cell death.
His Cell biology research includes themes of Neurotrophic factors and Biochemistry, Gene.
His Neuroscience research incorporates elements of Glutamate receptor and CREB.
Steven Finkbeiner has researched Neurodegeneration in several fields, including DNAJA3 and Amyotrophic lateral sclerosis.
As a member of one scientific family, Steven Finkbeiner mostly works in the field of Mutant, focusing on Mutation and, on occasion, Stem cell and Autophagy.
His work deals with themes such as Autophagosome, MAP1LC3B, Sequestosome 1, Computational biology and Physiology, which intersect with Programmed cell death.
His most cited work include:
- Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (4170 citations)
- Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (4170 citations)
- Guidelines for the use and interpretation of assays for monitoring autophagy (3242 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Neuroscience, Cell biology, Neurodegeneration, Huntingtin and Disease.
The various areas that Steven Finkbeiner examines in his Neuroscience study include Synaptic plasticity, Amyotrophic lateral sclerosis, Cell type and Induced pluripotent stem cell.
His studies deal with areas such as Autophagy, Genetics, Neurotrophic factors, Mutant and Inclusion bodies as well as Cell biology.
His Autophagy research includes elements of Lysosome and Neuroprotection.
His Neurodegeneration research is multidisciplinary, relying on both Frontotemporal dementia, Proteostasis, Biochemistry, Molecular biology and Programmed cell death.
Steven Finkbeiner specializes in Huntingtin, namely Huntingtin Protein.
He most often published in these fields:
- Neuroscience (42.93%)
- Cell biology (43.98%)
- Neurodegeneration (39.79%)
What were the highlights of his more recent work (between 2016-2021)?
- Neuroscience (42.93%)
- Cell biology (43.98%)
- Neurodegeneration (39.79%)
In recent papers he was focusing on the following fields of study:
Steven Finkbeiner focuses on Neuroscience, Cell biology, Neurodegeneration, Autophagy and Disease.
His studies in Neuroscience integrate themes in fields like Synaptic plasticity, Huntington's disease and Homeostatic plasticity.
His research in Cell biology intersects with topics in Stress granule, Huntingtin, Neuron and Phenotype.
His study in Neurodegeneration is interdisciplinary in nature, drawing from both Pathogenesis, Parkinson's disease, Alpha-synuclein, Single-cell analysis and Proteostasis.
His Autophagy study combines topics in areas such as Loss function, Lysosome, Frontotemporal dementia, Neuronal ceroid lipofuscinosis and Haploinsufficiency.
His Programmed cell death research is multidisciplinary, incorporating elements of Chaperone-mediated autophagy, Autolysosome and Knowledge base.
Between 2016 and 2021, his most popular works were:
- Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies (353 citations)
- In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images (242 citations)
- In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images (242 citations)
In his most recent research, the most cited papers focused on:
Steven Finkbeiner mostly deals with Computational biology, Artificial intelligence, Deep learning, Pattern recognition and Systems biology.
The study incorporates disciplines such as Gene Discovery, Genome, Intellectual disability, Autolysosome and Als gene in addition to Computational biology.
His Artificial intelligence study integrates concerns from other disciplines, such as In silico, Cell state and Antibody labeling.
His study in Deep learning is interdisciplinary in nature, drawing from both Artificial neural network, Pixel and Hoechst stain.
Steven Finkbeiner integrates Pattern recognition with Focus in his research.
The concepts of his Systems biology study are interwoven with issues in Infectious disease, Genomic data, Interactome and Neurodevelopmental disorder.
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