Related papers: How shall we use the proteomics toolbox for biomar…
Phenomenological screening of small molecule libraries for anticancer activity yields potentially interesting candidate molecules, with a bottleneck in the determination of drug targets and the mechanism of anticancer action. A novel…
This unit describes strategies for studying the proteomes of organelles, which is one example of targeted proteomics. It relies heavily on previously published units dealing with organelle preparation, protein solubilization, and proteomics…
Motivation: Biomarker discovery from high-dimensional data is a crucial problem with enormous applications in biology and medicine. It is also extremely challenging from a statistical viewpoint, but surprisingly few studies have…
Deep learning is an advanced technology that relies on large-scale data and complex models for feature extraction and pattern recognition. It has been widely applied across various fields, including computer vision, natural language…
A common goal in modern biostatistics is to form a biomarker signature from high dimensional gene expression data that is predictive of some outcome of interest. After learning this biomarker signature, an important question to answer is…
The human-associated microbiome is closely tied to human health and is of substantial clinical interest. Metagenomics-based tools are emerging for clinical diagnostics, tracking the spread of diseases, and surveillance of potential…
Machine learning brings the hope of finding new biomarkers extracted from cohorts with rich biomedical measurements. A good biomarker is one that gives reliable detection of the corresponding condition. However, biomarkers are often…
The problem of dynamic prediction with time-dependent covariates, given by biomarkers, repeatedly measured over time, has received much attention over the last decades. Two contrasting approaches have become in widespread use. The first is…
The multiple-biomarker classifier problem and its assessment are reviewed against the background of some fundamental principles from the field of statistical pattern recognition, machine learning, or the recently so-called "data science". A…
The convergent interests of different scientific disciplines, from biochemistry to electronics, toward the investigation of protein electrical properties, has promoted the development of a novel bailiwick, the so called proteotronics. The…
Model biomembrane systems play a crucial role in advancing biomedical research by providing simplified yet effective platforms for exploring complex biological mechanisms. These systems span a wide range of scales, from…
The full understanding of cellular functions requires information about protein numbers for various biomolecular assemblies and their dynamics, which can be partly accessed by super-resolution fluorescence microscopy. Yet, many protein…
Motivation: Metabolomics data is typically scaled to a common reference like a constant volume of body fluid, a constant creatinine level, or a constant area under the spectrum. Such normalization of the data, however, may affect the…
This paper reflects on the effect of several categories of medical conditions on human voice, focusing on those that may be hypothesized to have effects on voice, but for which the changes themselves may be subtle enough to have eluded…
Feature selection is a pattern recognition approach to choose important variables according to some criteria to distinguish or explain certain phenomena. There are many genomic and proteomic applications which rely on feature selection to…
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…
The ultimate target of proteomics identification is to identify and quantify the protein in the organism. Mass spectrometry (MS) based on label-free protein quantitation has mainly focused on analysis of peptide spectral counts and ion peak…
All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide provocative projections for technologies to…
Two-dimensional electrophoresis of proteins has preceded, and accompanied, the birth of proteomics. Although it is no longer the only experimental scheme used in modern proteomics, it still has distinct features and advantages. The purpose…
Molecular and genomic properties are critical in selecting cancer treatments to target individual tumors, particularly for immunotherapy. However, the methods to assess such properties are expensive, time-consuming, and often not routinely…