Related papers: Fast Proteome Identification and Quantification fr…
Motivated by an open problem of validating protein identities in label-free shotgun proteomics work-flows, we present a testing procedure to validate class/protein labels using available measurements across instances/peptides. More…
Proteomics will celebrate its 20th year in 2014. In this relatively short period of time, it has invaded most areas of biology and its use will probably continue to spread in the future. These two decades have seen a considerable increase…
Peptide identification in mass spectrometry-based proteomics is crucial for understanding protein function and dynamics. Traditional database search methods, though widely used, rely on heuristic scoring functions and statistical…
The rapid evolution of molecular dynamics (MD) methods, including machine-learned dynamics, has outpaced the development of standardized tools for method validation. Objective comparison between simulation approaches is often hindered by…
Two-dimensional gel electrophoresis has been instrumental in the development of proteomics. Although it is no longer the exclusive scheme used for proteomics, its unique features make it a still highly valuable tool, especially when…
Protein identification and profiling is critical for the advancement of cell and molecular biology as well as medical diagnostics. Although mass spectrometry and protein microarrays are commonly used for protein identification, both methods…
In the post-genome era, biologists have sought to measure the complete complement of proteins, termed proteomics. Currently, the most effective method to measure the proteome is with shotgun, or bottom-up, proteomics, in which the proteome…
In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases…
This paper presents an approach to the evaluation and validation of mass spectrometry data for construction of an `early warning' diagnostic procedure. We describe implementation of a designed experiment and place emphasis on the consistent…
Protein function does not solely depend on structure but often relies on dynamical transitions between distinct conformations. Despite this fact, our ability to characterize or predict protein dynamics is substantially less developed…
Mass spectrometry (MS) is essential for protein analysis but faces significant challenges with large datasets and complex post-translational modifications, resulting in difficulties in spectral identification. Open Modification Search (OMS)…
Understanding protein solubility is essential for their functional applications. Computational methods for predicting protein solubility are crucial for reducing experimental costs and enhancing the efficiency and success rates of protein…
Studying the pathways of ligand-receptor binding is essential to understand the mechanism of target recognition by small molecules. The binding free energy and kinetics of protein-ligand complexes can be computed using molecular dynamics…
Composed of amino acid chains that influence how they fold and thus dictating their function and features, proteins are a class of macromolecules that play a central role in major biological processes and are required for the structure,…
We consider the certification of temporal quantum correlations using the pseudo-density matrix (PDM), an extension of the density matrix to the time domain, where negative eigenvalues are key indicators of temporal correlations.…
Early detection of melanoma is crucial for improving survival rates. Current detection tools often utilize data-driven machine learning methods but often overlook the full integration of multiple datasets. We combine publicly available…
The limits of molecular dynamics (MD) simulations of macromolecules are steadily pushed forward by the relentless developments of computer architectures and algorithms. This explosion in the number and extent (in size and time) of MD…
We investigate whether synthetic images generated by diffusion models can enhance multi-label classification of protein subcellular localization. Specifically, we implement a simplified class-conditional denoising diffusion probabilistic…
Several processes in the cell, such as gene regulation, start when key proteins recognise and bind to short DNA sequences. However, as these sequences can be hundreds of million times shorter than the genome, they are hard to find by simple…
Mass spectrometry provides a high-throughput approach to identify proteins in biological samples. A key step in the analysis of mass spectrometry data is to identify the peptide sequence that, most probably, gave rise to each observed…