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Andras Fiser

Researcher at Albert Einstein College of Medicine

Publications -  139
Citations -  14919

Andras Fiser is an academic researcher from Albert Einstein College of Medicine. The author has contributed to research in topics: Protein structure & Peptide sequence. The author has an hindex of 46, co-authored 127 publications receiving 13520 citations. Previous affiliations of Andras Fiser include Alfréd Rényi Institute of Mathematics & Yeshiva University.

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Journal ArticleDOI

Comparative protein structure modeling of genes and genomes

TL;DR: There is a need to develop an automated, rapid, robust, sensitive, and accurate comparative modeling pipeline applicable to whole genomes and to encourage new kinds of applications for the many resulting models, based on their large number and completeness at the level of the family, organism, or functional network.
Journal ArticleDOI

Modeling of loops in protein structures.

TL;DR: A new automated modeling technique that significantly improves the accuracy of loop predictions in protein structures by predicting loops of known structure in only approximately correct environments with errors typical of comparative modeling without misalignment is described.
Book ChapterDOI

Modeller: generation and refinement of homology-based protein structure models.

TL;DR: This work states that functional characterization of a protein sequence is one of the most frequent problems in biology and comparative or homology modeling can sometimes provide a useful 3D model for a protein (target) that is related to at least one known protein structure (template).
Journal ArticleDOI

Protein production and purification.

Susanne Gräslund, +86 more
- 01 Feb 2008 - 
TL;DR: This review presents methods that could be applied at the outset of any project, a prioritized list of alternate strategies and a list of pitfalls that trip many new investigators.
Journal ArticleDOI

ModLoop: automated modeling of loops in protein structures

TL;DR: ModLoop is a web server for automated modeling of loops in protein structures that predicts the loop conformations by satisfaction of spatial restraints, without relying on a database of known protein structures.