What is he best known for?
The fields of study he is best known for:
His primary areas of study are Peptide, Biochemistry, Biophysics, Stereochemistry and Peptide synthesis.
The study incorporates disciplines such as Combinatorial chemistry, Peptide library, Peptide sequence and Transferrin receptor in addition to Peptide.
His Biochemistry study which covers Drug delivery that intersects with Cell-penetrating peptide and Internalization.
His Biophysics research is multidisciplinary, incorporating perspectives in Protein structure, Colloidal gold, Blood–brain barrier and Amyloid.
In his research on the topic of Stereochemistry, Reactivity is strongly related with Molecule.
His Peptide synthesis study is focused on Amino acid in general.
His most cited work include:
- Chemical Approaches to the Synthesis of Peptides and Proteins (407 citations)
- Molecular recycling within amyloid fibrils. (309 citations)
- Perspectives on NMR in drug discovery: a technique comes of age (297 citations)
What are the main themes of his work throughout his whole career to date?
Ernest Giralt focuses on Peptide, Stereochemistry, Biochemistry, Combinatorial chemistry and Peptide synthesis.
His Peptide research focuses on subjects like Biophysics, which are linked to Colloidal gold.
His work deals with themes such as Cyclic peptide, Side chain, Molecule and Cysteine, which intersect with Stereochemistry.
His study ties his expertise on Drug delivery together with the subject of Biochemistry.
His studies in Combinatorial chemistry integrate themes in fields like Organic chemistry and Solid-phase synthesis.
His Peptide synthesis research incorporates elements of Protecting group and Phase.
He most often published in these fields:
- Peptide (36.19%)
- Stereochemistry (31.99%)
- Biochemistry (15.73%)
What were the highlights of his more recent work (between 2013-2021)?
- Peptide (36.19%)
- Biophysics (9.97%)
- Biochemistry (15.73%)
In recent papers he was focusing on the following fields of study:
Peptide, Biophysics, Biochemistry, Blood–brain barrier and Cell biology are his primary areas of study.
The concepts of his Peptide study are interwoven with issues in In vitro, Drug delivery, Receptor, Protein–protein interaction and In vivo.
His research integrates issues of Colloidal gold, Endocytosis, DNA and Photothermal therapy in his study of Biophysics.
Ernest Giralt studies Protease, a branch of Biochemistry.
His research on Blood–brain barrier also deals with topics like
- Peptidomimetic that connect with fields like Apamin,
- Membrane and related Amino acid, Drug delivery to the brain, Bicyclic molecule, Nanotechnology and Peptide synthesis.
Ernest Giralt focuses mostly in the field of Amino acid, narrowing it down to topics relating to Stereochemistry and, in certain cases, Protein dynamics.
Between 2013 and 2021, his most popular works were:
- Blood–brain barrier shuttle peptides: an emerging paradigm for brain delivery (151 citations)
- Three Valuable Peptides from Bee and Wasp Venoms for Therapeutic and Biotechnological Use: Melittin, Apamin and Mastoparan (147 citations)
- Modulating protein–protein interactions: the potential of peptides (133 citations)
In his most recent research, the most cited papers focused on:
Ernest Giralt spends much of his time researching Peptide, Blood–brain barrier, Biochemistry, Biophysics and Computational biology.
His Peptide research includes themes of Nucleic acid, Circular dichroism, In vivo and Protein–protein interaction.
The study of Biochemistry is intertwined with the study of Drug delivery in a number of ways.
His Biophysics research is multidisciplinary, relying on both Nanotechnology, Central nervous system, DNA, Membrane and Stereochemistry.
Ernest Giralt performs integrative Stereochemistry and Context research in his work.
His study on Computational biology also encompasses disciplines like
- Intracellular, Chemical biology, Combinatorial chemistry and Identification methods most often made with reference to Internalization,
- Intestinal absorption that intertwine with fields like Pharmacology.
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.
