His main research concerns Chondrocyte, Biophysics, Mechanotransduction, Anatomy and Glycosaminoglycan. His Chondrocyte research integrates issues from Tissue engineering, Cell biology and Agarose. His studies deal with areas such as Phenotype and Cell as well as Cell biology.
His research integrates issues of Proteoglycan, Compressive strength and Deformation in his study of Biophysics. His Mechanotransduction research is multidisciplinary, incorporating perspectives in Self-healing hydrogels, Nucleus and Cytoskeleton. The various areas that David A. Lee examines in his Anatomy study include Confocal microscopy, Compression, Cell membrane and Deformation.
David A. Lee mainly investigates Cell biology, Chondrocyte, Mechanotransduction, Biophysics and Anatomy. His Cell biology research includes themes of Cell, In vitro and Cellular differentiation. His study in Chondrocyte is interdisciplinary in nature, drawing from both Deformation, Glycosaminoglycan and Agarose.
His studies in Mechanotransduction integrate themes in fields like Cell growth, Stimulation, Cytoskeleton, Extracellular matrix and Biomedical engineering. David A. Lee has included themes like Fibroblast, Self-healing hydrogels and Nanotechnology in his Biophysics study. His work investigates the relationship between Anatomy and topics such as Confocal microscopy that intersect with problems in Confocal.
David A. Lee focuses on Cell biology, Computational biology, Mechanotransduction, Annotation and GPER. His work in Cell biology addresses issues such as Chromatin, which are connected to fields such as Purinergic receptor. His Computational biology research incorporates elements of Bioinformatics, Protein domain, UniProt, Protein function and Molecular Sequence Annotation.
Bioinformatics is closely attributed to Genome in his research. His biological study spans a wide range of topics, including Surgery, Chondrocyte, Stimulation and Matrix metalloproteinase. Chondrocyte and Poisson's ratio are two areas of study in which David A. Lee engages in interdisciplinary research.
David A. Lee mostly deals with Computational biology, Bioinformatics, Molecular Sequence Annotation, Annotation and Cell biology. His Computational biology research is multidisciplinary, relying on both Protein structure and Protein function. His Bioinformatics study integrates concerns from other disciplines, such as Protein domain and Genome.
The concepts of his Annotation study are interwoven with issues in Machine learning and Data set. His Cell biology study frequently intersects with other fields, such as Collagen receptor. His Mesenchymal stem cell study incorporates themes from Lamin, Mechanotransduction, Stem cell and Cellular differentiation.
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Predicting protein function from sequence and structure
David Lee;Oliver Redfern;Christine Orengo.
Nature Reviews Molecular Cell Biology (2007)
Compressive strains at physiological frequencies influence the metabolism of chondrocytes seeded in agarose.
David A. Lee;Dan L. Bader.
Journal of Orthopaedic Research (1997)
CATH: comprehensive structural and functional annotations for genome sequences
Ian Sillitoe;Tony E. Lewis;Alison L. Cuff;Sayoni Das.
Nucleic Acids Research (2015)
The CATH Domain Structure Database and related resources Gene3D and DHS provide comprehensive domain family information for genome analysis
Frances M. G. Pearl;Annabel E. Todd;Ian Sillitoe;Mark Dibley.
Nucleic Acids Research (2004)
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur.
Genome Biology (2016)
Quantification of Sulfated Glycosaminoglycans in Chondrocyte/Alginate Cultures, by Use of 1,9-Dimethylmethylene Blue
Brian O. Enobakhare;Dan L. Bader;David A. Lee.
Analytical Biochemistry (1996)
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur.
arXiv: Quantitative Methods (2016)
Crosslinking density influences chondrocyte metabolism in dynamically loaded photocrosslinked poly(ethylene glycol) hydrogels.
Stephanie J. Bryant;Tina T. Chowdhury;David A. Lee;Dan L. Bader.
Annals of Biomedical Engineering (2004)
CATH: an expanded resource to predict protein function through structure and sequence.
Natalie L. Dawson;Tony E. Lewis;Sayoni Das;Jonathan G. Lees.
Nucleic Acids Research (2017)
The metabolism of human mesenchymal stem cells during proliferation and differentiation.
Girish Pattappa;Hannah K. Heywood;Joost D. de Bruijn;David A. Lee.
Journal of Cellular Physiology (2011)
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