Results 101 to 110 of about 2,642,890 (372)
To address the issues of fluid loss and tough texture in Antarctic krill meat, the impact of soaking times and solutions of varying ionic strengths (0.8, 0.9, 1.0, and 1.1 mol/L) on the properties of myofibrillar proteins (MPs) and water-holding capacity
Xiaofang LIU +5 more
doaj +1 more source
Nanoplasmonic mid-infrared biosensor for in vitro protein secondary structure detection
Plasmonic nanoantennas offer new applications in mid-infrared (mid-IR) absorption spectroscopy with ultrasensitive detection of structural signatures of biomolecules, such as proteins, due to their strong resonant near-fields.
D. Etezadi +5 more
semanticscholar +1 more source
AZD9291 has shown promise in targeted cancer therapy but is limited by resistance. In this study, we employed metabolic labeling and LC–MS/MS to profile time‐resolved nascent protein perturbations, allowing dynamic tracking of drug‐responsive proteins. We demonstrated that increased NNMT expression is associated with drug resistance, highlighting NNMT ...
Zhanwu Hou +5 more
wiley +1 more source
This study reports the effect of pH (2, 7, 10) and heat treatment (80 °C for 30 min) on the oil–water (o/w) interfacial behavior of hemp seed protein isolate (HPI) aqueous dispersions.
Davide Odelli +6 more
doaj +1 more source
This study aimed to investigate the variation of molecular functional properties of peanut protein isolate (PPI) over the storage process and reveal the correlation between the PPI secondary structure and properties in the storage procedure.
Xiaotong Sun +5 more
doaj +1 more source
A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira +14 more
wiley +1 more source
Secondary Protein Structure Prediction Using Neural Networks [PDF]
Sidharth Malhotra, Robin Walters
openalex +1 more source
DeepPrime2Sec: Deep Learning for Protein Secondary Structure Prediction from the Primary Sequences
Motivation Here we investigate deep learning-based prediction of protein secondary structure from the protein primary sequence. We study the function of different features in this task, including one-hot vectors, biophysical features, protein sequence ...
Ehsaneddin Asgari +3 more
semanticscholar +1 more source
This study indicates that Merkel cell carcinoma (MCC) does not originate from Merkel cells, and identifies gene, protein & cellular expression of immune‐linked and neuroendocrine markers in primary and metastatic Merkel cell carcinoma (MCC) tumor samples, linked to Merkel cell polyomavirus (MCPyV) status, with enrichment of B‐cell and other immune cell
Richie Jeremian +10 more
wiley +1 more source
Protein Secondary Structure Prediction Based on Data Partition and Semi-Random Subspace Method
Protein secondary structure prediction is one of the most important and challenging problems in bioinformatics. Machine learning techniques have been applied to solve the problem and have gained substantial success in this research area. However there is
Yuming Ma, Yihui Liu, Jinyong Cheng
semanticscholar +1 more source

