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PASTA / Prediction of Amyloid StrucTure Aggregation
Determines protein aggregation from sequence. PASTA can evaluate the effect of point-mutations on the aggregation profile. It annotates each sequence with aggregation-prone regions, alpha-helix, beta-strand, coil and intrinsic disordered regions. This tool is able to identify secondary structure using a machine learning algorithm. It enables the study of pathogenic mutations and of cross-amyloid interactions between protein heterodimers.
Allows reconstruction of s β-serpentine arrangements from individual β-arches. BetaSerpentine predicts possible β-serpentine arrangements of adjacent β-arches and ranks them based on the newly developed scores in order of preference. The purpose of this tool is reconstruction of all possible β-serpentine arrangements within an analyzed protein sequence. User can specify two thresholds: (1) for the ArchCandy scores of individual β-arches that are used for β-serpentines construction, and (2) for the general β-serpentine score.
Estimates mass per unit length (MPL) for fibrilar biological assemblies. MpUL-multi is a standalone software, developed for rapid MPL estimation, allowing for the semi-automated processing of tilted beam transmission electron microscopy (TB-TEM) data from dark field imaging through a graphical interface. The application is able to average values from multiple standards to reduce variability due to differences in the intensity measured from Tobacco Mosaic Virus (TMV) molecules.
APPNN / Amyloid propensity prediction neural network
An amyloidogenicity propensity predictor based on a machine learning approach through recursive feature selection and feed-forward neural networks, taking advantage of newly published sequences with experimental, in vitro, evidence of amyloid formation. APPNN allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔG° values for peptides extrapolated in 0 M urea).
Generates structural models for any amyloid fibril, starting from its sequence. Fibpredictor is a computational procedure that identifies energetically favorable class of amyloid fibril for a peptide sequence, or whether equally favorable amyloid fibril structures for the same sequence exist. Results are combined with experimental data to determine the sense of amyloid b-spine to reduce the analysis to a small subset of fibril classes. In such cases, Fibpredictor demonstrated the ability to identify the correct amyloid fibril structures among top-ranked conformations
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