What is he best known for?
The fields of study he is best known for:
Salvador Ventura mainly investigates Biochemistry, Protein folding, Protein aggregation, Inclusion bodies and Protein structure.
His Protein folding study incorporates themes from Crystallography, Biophysics, Mutant, Chaperone and Function.
His research integrates issues of Folding, Protein sequencing, Green fluorescent protein and Amyloid in his study of Protein aggregation.
His work carried out in the field of Inclusion bodies brings together such families of science as Cell, Biological activity, Protein quality and Protein biosynthesis.
His Protein structure study combines topics from a wide range of disciplines, such as Amino acid, Globular protein, Plasma protein binding and Computational biology.
His study in Computational biology is interdisciplinary in nature, drawing from both Oxidation reduction, BECN1, Disulfide bond, Oxidative folding and Physiology.
His most cited work include:
- Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (4170 citations)
- AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides (605 citations)
- Protein quality in bacterial inclusion bodies (301 citations)
What are the main themes of his work throughout his whole career to date?
Salvador Ventura mainly focuses on Protein aggregation, Biochemistry, Amyloid, Protein folding and Biophysics.
His studies deal with areas such as Globular protein, Computational biology, Intracellular and Protein biosynthesis as well as Protein aggregation.
Within one scientific family, he focuses on topics pertaining to Proteome under Computational biology, and may sometimes address concerns connected to Proteomics.
His Amyloid research includes themes of Fibril, Peptide and Bacteria.
His Protein folding research incorporates themes from Protein structure, Cell, Chaperone and Folding.
He has researched Biophysics in several fields, including Self-assembly and Protein engineering.
He most often published in these fields:
- Protein aggregation (44.09%)
- Biochemistry (39.76%)
- Amyloid (33.86%)
What were the highlights of his more recent work (between 2018-2021)?
- Protein aggregation (44.09%)
- Biophysics (25.59%)
- Amyloid (33.86%)
In recent papers he was focusing on the following fields of study:
Salvador Ventura focuses on Protein aggregation, Biophysics, Amyloid, Computational biology and Cell biology.
Salvador Ventura has included themes like Protein structure, Intrinsically disordered proteins, Protein solubility and Small molecule in his Protein aggregation study.
The study incorporates disciplines such as Nanoparticle, Protein engineering, α synuclein and Thioflavin in addition to Biophysics.
The concepts of his Amyloid study are interwoven with issues in Biofilm matrix, Adaptation, Fusion protein and Longevity.
He has included themes like Amino acid, Rational design, Beta, In silico and Supersecondary structure in his Computational biology study.
His Cell biology study combines topics from a wide range of disciplines, such as Phenotype, Oxidative stress, Folding and Yeast.
Between 2018 and 2021, his most popular works were:
- DisProt: intrinsic protein disorder annotation in 2020. (51 citations)
- Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility. (24 citations)
- C-mannosylation supports folding and enhances stability of thrombospondin repeats (19 citations)
In his most recent research, the most cited papers focused on:
Salvador Ventura mainly focuses on Protein aggregation, Biophysics, Amyloid, Cell biology and Computational biology.
His Protein aggregation research incorporates themes from Parkinson's disease, Protein solubility and Small molecule.
His Biophysics study integrates concerns from other disciplines, such as Covalent bond, Neurotoxicity, Protein engineering and Druggability.
The various areas that Salvador Ventura examines in his Amyloid study include Ribonucleoprotein, Alternative splicing, Gene isoform, Muscular dystrophy and Cell wall.
His Cell biology research incorporates elements of Cell, Gene expression and Yeast.
Salvador Ventura connects Computational biology with Low complexity in his study.
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