Related papers: Starr: Simple Tiling Array Analysis of Affymetrix …
Modern deep learning implementations for medical imaging usually rely on large labeled datasets. These datasets are often difficult to obtain due to privacy concerns, high costs, and even scarcity of cases. In this paper, a label-efficient…
Prediction of protein-ligand interactions (PLI) plays a crucial role in drug discovery as it guides the identification and optimization of molecules that effectively bind to target proteins. Despite remarkable advances in deep…
High throughput genome sequencing technologies such as RNA-Seq and Microarray have the potential to transform clinical decision making and biomedical research by enabling high-throughput measurements of the genome at a granular level.…
Protein-protein and protein nucleic acid interactions are vitally important for a wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses. We have…
We present an overview of Sherpa, an open source Python project, and discuss its development history, broad design concepts and capabilities. Sherpa contains powerful tools for combining parametric models into complex expressions that can…
Spatial transcriptomics (ST) is a promising technique that characterizes the spatial gene profiling patterns within the tissue context. Comprehensive ST analysis depends on consecutive slices for 3D spatial insights, whereas the missing…
Nucleic acid sensing is crucial for advancing diagnostics, therapeutic monitoring and molecu-lar biology research, by enabling the precise identification of DNA and RNA interactions. Here, we present an innovative sensing platform based on…
We present a semi-empirical spectral classification scheme for normal B-type stars using near-infrared spectra (1.5-1.7 $\mu$m) from the SDSS APOGEE2-N DR14 database. The main motivation for working with B-type stars is their importance in…
Microarrays have been developed that tile the entire nonrepetitive genomes of many different organisms, allowing for the unbiased mapping of active transcription regions or protein binding sites across the entire genome. These tiling array…
SHARK-NIR is a new compact instrument for coronagraphic imaging, direct imaging, and coronagraphic spectroscopy in the near-infrared wavelengths mounted at LBT. Taking advantage of the telescope's adaptive optics system, it provides high…
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…
Diffuse envelopes around Mira variables are among the most important sources influencing the chemical evolution of galaxies. However they represent an observational challenge because of their complex spectral features and their rapid…
Iris recognition systems are vulnerable to the presentation attacks, such as textured contact lenses or printed images. In this paper, we propose a lightweight framework to detect iris presentation attacks by extracting multiple…
In explainable artificial intelligence, discriminative feature localization is critical to reveal a blackbox model's decision-making process from raw data to prediction. In this article, we use two real datasets, the MNIST handwritten…
We present the Core Imaging Library (CIL), an open-source Python framework for tomographic imaging with particular emphasis on reconstruction of challenging datasets. Conventional filtered back-projection reconstruction tends to be…
The STAR experiment at the Relativistic Heavy-Ion Collider (RHIC) at Brookhaven National Laboratory (BNL) is carrying out a spin physics program colliding transverse or longitudinal polarized proton beams at $\sqrt{s}=200-500 $GeV to gain a…
Protein (receptor)--ligand interaction prediction is a critical component in computer-aided drug design, significantly influencing molecular docking and virtual screening processes. Despite the development of numerous scoring functions in…
Automated analysis of Pap smear images is critical for cervical cancer screening but remains challenging due to dense cell distribution and complex morphology. In this paper, we present our winning solution for the RIVA Cervical Cytology…
The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite these strides, its application in protein inference is impeded by the scarcity of…
We present a theoretical model of facilitated diffusion of proteins in the cell nucleus. This model, which takes into account the successive binding/unbinding events of proteins to DNA, relies on a fractal description of the chromatin which…