The amount of public proteomics data is rapidly increasing but there is no standardized format
to describe the sample metadata and their relationship with the dataset files in a way that …

In recent years machine learning has made extensive progress in modeling many aspects
of mass spectrometry data. We brought together proteomics data generators, repository …

Highlights • Complex regulatory interactions ensure female-specific monoallelic Xist
expression. • Stochastic upregulation combined with a negative feedback can explain the Xist …

The majority of mass spectrometry-based protein quantification studies uses peptide-centric
analytical methods and thus strongly relies on efficient and unbiased protein digestion …

Motivation: Fuzzy c-means clustering is widely used to identify cluster structures in high-dimensional
datasets, such as those obtained in DNA microarray and quantitative proteomics …

Background Before the advent of an effective vaccine, nonpharmaceutical interventions, such
as mask-wearing, social distancing, and lockdowns, have been the primary measures to …

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to
improvement in human health, agriculture and the environment. In support of these …

We describe a method that combines an optimized titanium dioxide protocol and hydrophilic
interaction liquid chromatography to simultaneously enrich, identify and quantify …

Barchan sand dunes are highly mobile, crescent-shaped dunes that occur in areas where
sand is sparse and the wind is unidirectional. Here we show mathematically how two such …

A general type of nonlinear Fokker-Planck equation is derived directly from a master equation,
by introducing generalized transition rates. The H theorem is demonstrated for systems …