Her primary areas of investigation include Genetics, microRNA, Gene, Computational biology and Small RNA. Her research in the fields of Morphogenesis, Embryonic stem cell and Gene regulatory network overlaps with other disciplines such as Blastoderm and Reaper. Debora S. Marks has included themes like Psychological repression, Molecular biology, Gene silencing and Regulation of gene expression in her microRNA study.
Her Gene silencing research includes themes of Translational regulation and Gene expression profiling. Her Gene study frequently links to related topics such as Supplementary data. Her Computational biology study incorporates themes from Transcriptome, Sequence analysis, DNA, Protein structure and De novo protein structure prediction.
Debora S. Marks focuses on Computational biology, Genetics, Gene, Protein structure and microRNA. Her Computational biology study combines topics in areas such as RNA, Principle of maximum entropy, Function, Protein structure prediction and Sequence. Her RNA study combines topics from a wide range of disciplines, such as Sequence analysis and Sequence.
Her Genetics research integrates issues from De novo protein structure prediction and Threading. Her study in Protein structure is interdisciplinary in nature, drawing from both Amino acid, Plasma protein binding, Transmembrane protein, Protein family and Biological system. Her microRNA research is multidisciplinary, incorporating elements of Gene expression, Molecular biology, Messenger RNA, Cell biology and Regulation of gene expression.
Her primary areas of study are Computational biology, Artificial intelligence, Sequence, Machine learning and Protein structure. The Computational biology study combines topics in areas such as RNA, Recombinant DNA, Saccharomyces cerevisiae and Protein–protein interaction. Her Artificial intelligence study deals with Variable intersecting with Expression, Generative model, Sequence space, Protein design and Leverage.
Her Machine learning research incorporates themes from Network model and Computational model. Her Protein structure research is multidisciplinary, relying on both Plasma protein binding, Epistasis, Mutant, Sequence and Protein family. Her biological study focuses on Gene.
The scientist’s investigation covers issues in RNA, Computational biology, Epistasis, Autoregressive model and Leverage. She has researched RNA in several fields, including WW domain, Mutant, Mutation, Sequence and Protein structure. Her studies deal with areas such as Transmembrane protein, Peptidoglycan, Cell wall, Transmembrane domain and Thermus thermophilus as well as Protein structure.
Her work carried out in the field of Computational biology brings together such families of science as Missense mutation, Complementarity determining region, Generative grammar, Genetic variation and Ribozyme. Her research on Epistasis concerns the broader Gene. The concepts of her Leverage study are interwoven with issues in Sequence space and Generative model.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Human MicroRNA targets.
Bino John;Anton James Enright;Anton James Enright;Alexei Aravin;Thomas Tuschl.
PLOS Biology (2004)
MicroRNA targets in Drosophila
Anton J Enright;Bino John;Ulrike Gaul;Thomas Tuschl.
Genome Biology (2003)
The microRNA.org resource: targets and expression
Doron Betel;Manda Wilson;Aaron P Gabow;Debora S. Marks.
Nucleic Acids Research (2007)
Identification of Virus-Encoded MicroRNAs
Sébastien Pfeffer;Mihaela Zavolan;Friedrich A. Grässer;Minchen Chien.
Direct-coupling analysis of residue coevolution captures native contacts across many protein families
Faruck Morcos;Andrea Pagnani;Bryan Lunt;Arianna Bertolino.
Proceedings of the National Academy of Sciences of the United States of America (2011)
The small RNA profile during Drosophila melanogaster development
Alexei A. Aravin;Mariana Lagos-Quintana;Abdullah Yalcin;Mihaela Zavolan.
Developmental Cell (2003)
miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and may downregulate the high affinity cationic amino acid transporter CAT-1.
Jinhong Chang;Emmanuelle Nicolas;Debora Marks;Chris Sander.
RNA Biology (2004)
Protein 3D Structure Computed from Evolutionary Sequence Variation
Debora S. Marks;Lucy J. Colwell;Robert Sheridan;Thomas A. Hopf.
PLOS ONE (2011)
Protein structure prediction from sequence variation
Debora S Marks;Thomas A Hopf;Chris Sander.
Nature Biotechnology (2012)
Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs
Aly A Khan;Doron Betel;Martin L Miller;Martin L Miller;Chris Sander.
Nature Biotechnology (2009)
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