His scientific interests lie mostly in Genetics, Computational biology, Protein structure, Phylogenetic tree and Phylogenetics. Tal Pupko combines subjects such as Amino acid, Identification and Function with his study of Computational biology. His Function research incorporates elements of Biochemistry and Multiple sequence alignment.
His study in Protein structure is interdisciplinary in nature, drawing from both Protein Biochemistry, Biophysics, Sequence analysis and Conserved sequence. His research investigates the connection with Phylogenetic tree and areas like Data mining which intersect with concerns in Tree, Robustness, Inference and Statistical hypothesis testing. His research in Phylogenetics intersects with topics in Entomology and Evolutionary biology.
Tal Pupko mainly investigates Genetics, Computational biology, Phylogenetics, Phylogenetic tree and Gene. His studies examine the connections between Genetics and genetics, as well as such issues in Inference, with regards to Bioinformatics, Probabilistic logic and Pattern recognition. His Computational biology research incorporates themes from Protein structure, Amino acid and Epitope, Antibody.
The concepts of his Protein structure study are interwoven with issues in Sequence analysis and Conserved sequence. His Phylogenetics research integrates issues from Evolutionary biology and Function. His work on Phyletic gradualism as part of general Phylogenetic tree study is frequently connected to Set, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His primary scientific interests are in Algorithm, Computational biology, Inference, Phylogenetic tree and Model selection. Tal Pupko works mostly in the field of Algorithm, limiting it down to topics relating to Statistical model and, in certain cases, Clade, Task and Biological data. His work deals with themes such as Amino acid, Proteome and DNA sequencing, which intersect with Computational biology.
Tal Pupko has researched Inference in several fields, including Tree, Evolutionary dynamics and Probabilistic logic. His Tree research is multidisciplinary, incorporating perspectives in Multiple sequence alignment and Sequence alignment. His research integrates issues of Statistical inference, Phylogenetics and Selection in his study of Model selection.
Tal Pupko focuses on Algorithm, Phylogenetic tree, Sequence reconstruction, Model selection and Network topology. His Algorithm study integrates concerns from other disciplines, such as Multiple sequence alignment and Inference. His Phylogenetic tree research includes elements of Comparative genomics, Genomics, Sequence alignment and Bacterial genome size.
His Sequence reconstruction research overlaps with Simulated data, Phylogenetics and Rendering.
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ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules.
Haim Ashkenazy;Shiran Abadi;Eric Martz;Ofer Chay.
Nucleic Acids Research (2016)
ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids
Haim Ashkenazy;Elana Erez;Eric Martz;Tal Pupko.
Nucleic Acids Research (2010)
ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures
Meytal Landau;Itay Mayrose;Yossi Rosenberg;Fabian Glaser.
Nucleic Acids Research (2005)
ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information
Fabian Glaser;Tal Pupko;Inbal Paz;Rachel E. Bell.
GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters
Itamar Sela;Haim Ashkenazy;Kazutaka Katoh;Tal Pupko.
Nucleic Acids Research (2015)
Rate4Site: an algorithmic tool for the identification of functional regions in proteins by surface mapping of evolutionary determinants within their homologues
Tal Pupko;Rachel E. Bell;Itay Mayrose;Fabian Glaser.
intelligent systems in molecular biology (2002)
GUIDANCE: a web server for assessing alignment confidence scores
Osnat Penn;Eyal Privman;Haim Ashkenazy;Giddy Landan.
Nucleic Acids Research (2010)
ConSurf: Using Evolutionary Data to Raise Testable Hypotheses about Protein Function
Gershon Celniker;Guy Nimrod;Haim Ashkenazy;Fabian Glaser.
Israel Journal of Chemistry (2013)
ConSeq: the identification of functionally and structurally important residues in protein sequences
Carine Berezin;Fabian Glaser;Josef Rosenberg;Inbal Paz.
Comparison of Site-Specific Rate-Inference Methods for Protein Sequences: Empirical Bayesian Methods Are Superior
Itay Mayrose;Dan Graur;Nir Ben-Tal;Tal Pupko.
Molecular Biology and Evolution (2004)
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