AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Intracellular Space

Showing 11 to 19 of 19 articles

Clear Filters

iPHLoc-ES: Identification of bacteriophage protein locations using evolutionary and structural features.

Journal of theoretical biology
Bacteriophage proteins are viruses that can significantly impact on the functioning of bacteria and can be used in phage based therapy. The functioning of Bacteriophage in the host bacteria depends on its location in those host cells. It is very impo...

pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC.

Gene
Knowledge of subcellular locations of proteins is crucially important for in-depth understanding their functions in a cell. With the explosive growth of protein sequences generated in the postgenomic age, it is highly demanded to develop computationa...

HPSLPred: An Ensemble Multi-Label Classifier for Human Protein Subcellular Location Prediction with Imbalanced Source.

Proteomics
Predicting the subcellular localization of proteins is an important and challenging problem. Traditional experimental approaches are often expensive and time-consuming. Consequently, a growing number of research efforts employ a series of machine lea...

Protein subcellular localization prediction using multiple kernel learning based support vector machine.

Molecular bioSystems
Predicting the subcellular locations of proteins can provide useful hints that reveal their functions, increase our understanding of the mechanisms of some diseases, and finally aid in the development of novel drugs. As the number of newly discovered...

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins.

Computational intelligence and neuroscience
Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction...

Identifying the missing proteins in human proteome by biological language model.

BMC systems biology
BACKGROUND: With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and p...

MSLVP: prediction of multiple subcellular localization of viral proteins using a support vector machine.

Molecular bioSystems
Knowledge of the subcellular location (SCL) of viral proteins in the host cell is important for understanding their function in depth. Therefore, we have developed "MSLVP", a two-tier prediction algorithm for predicting multiple SCLs of viral protein...

Vision-based Nano Robotic System for High-throughput Non-embedded Cell Cutting.

Scientific reports
Cell cutting is a significant task in biology study, but the highly productive non-embedded cell cutting is still a big challenge for current techniques. This paper proposes a vision-based nano robotic system and then realizes automatic non-embedded ...

Predict Gram-Positive and Gram-Negative Subcellular Localization via Incorporating Evolutionary Information and Physicochemical Features Into Chou's General PseAAC.

IEEE transactions on nanobioscience
In this study, we used structural and evolutionary based features to represent the sequences of gram-positive and gram-negative subcellular localizations. To do this, we proposed a normalization method to construct a normalize Position Specific Scori...