OrgXenomics: an integrated proteomic knowledge base for patient-derived organoid and xenograft.

Patient-derived models (PDMs, particularly organoids and xenografts) are irreplaceable tools for precision medicine, from target development to lead identification, then to preclinical evaluation, and finally to clinical decision-making. So far, PDM-based proteomics has emerged to be one of the cutting-edge directions and massive data have been accumulated. However, such PDM-based proteomic data have not been provided by any of the available databases, and proteomics profiles of all proteins in proteomic study are also completely absent from existing databases.

SubCELL: the landscape of subcellular compartment-specific molecular interactions.

The subcellular compartment-specific molecular interactions (SCSIs) are the building blocks for most molecular functions, biological processes and disease pathogeneses. Extensive experiments have therefore been conducted to accumulate the valuable information of SCSIs, but none of the available databases has been constructed to describe those data. In this study, a novel knowledge base SubCELL is thus introduced to depict the landscape of SCSIs among DNAs/RNAs/proteins.

PDCdb: the biological activity and pharmaceutical information of peptide-drug conjugate (PDC).

Peptide-drug conjugates (PDCs) have emerged as a promising class of targeted therapeutics with substantial pharmaceutical advantages and market potentials, which is a combination of a peptide (selective to the disease-relevant target), a linker (stable in circulation but cleavable at target site) and a cytotoxic/radioactive drug (efficacious/traceable for disease). Among existing PDCs, those based on radiopharmaceuticals (a.k.

Mapping synthetic binding proteins epitopes on diverse protein targets by protein structure prediction and protein-protein docking.

Synthetic binding proteins (SBPs) are a class of artificial proteins engineered from privileged protein scaffolds, which can form highly specific molecular recognition interfaces with a variety of targets. Due to the characteristics of small size, high stability, and good tissue permeability, SBPs have important applications in biomedical research, disease diagnosis and treatment. However, knowledge of SBPs epitopes on the structures of target proteins is still limited, which hinder the development of novel SBPs.

[An unsupervised classification of hyperspectral images based on pixels reduction with spatial coherence property].

In order to improve classification and edge accuracy, PRSCP and linear regression analysis are introduced; a new algorithm of unsupervised classification based on PRSCP is proposed. The algorithm procedure starts with the similarity of pixel spectral, and then makes use of minimum related window to combine similar pixels spatially adjacent into a block. Linear expression is applied to model the spectral vector of pixels in the same block, and significance of the linear expression is verified by F-statistic.