AIMC Topic: Models, Biological

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Adaptive multinomial regression with overlapping groups for multi-class classification of lung cancer.

Computers in biology and medicine
Multi-class classification has attracted much attention in cancer diagnosis and treatment and many machine learning methods have emerged for addressing this issue recently. However, class imbalance and gene selection problems occur in classifying lun...

Fisher Discrimination Regularized Robust Coding Based on a Local Center for Tumor Classification.

Scientific reports
Tumor classification is crucial to the clinical diagnosis and proper treatment of cancers. In recent years, sparse representation-based classifier (SRC) has been proposed for tumor classification. The employed dictionary plays an important role in sp...

Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks.

Analytical biochemistry
Deep learning has been increasingly used to solve a number of problems with state-of-the-art performance in a wide variety of fields. In biology, deep learning can be applied to reduce feature extraction time and achieve high levels of performance. I...

Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks.

Neural computation
Biological networks have long been known to be modular, containing sets of nodes that are highly connected internally. Less emphasis, however, has been placed on understanding how intermodule connections are distributed within a network. Here, we bor...

Using Emulation to Engineer and Understand Simulations of Biological Systems.

IEEE/ACM transactions on computational biology and bioinformatics
Modeling and simulation techniques have demonstrated success in studying biological systems. As the drive to better capture biological complexity leads to more sophisticated simulators, it becomes challenging to perform statistical analyses that help...

Predictive modeling of treatment resistant depression using data from STAR*D and an independent clinical study.

PloS one
Identification of risk factors of treatment resistance may be useful to guide treatment selection, avoid inefficient trial-and-error, and improve major depressive disorder (MDD) care. We extended the work in predictive modeling of treatment resistant...

HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.

RNA biology
LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models des...

Patient Similarity Networks for Precision Medicine.

Journal of molecular biology
Clinical research and practice in the 21st century is poised to be transformed by analysis of computable electronic medical records and population-level genome-scale patient profiles. Genomic data capture genetic and environmental state, providing in...

Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

BMC cancer
BACKGROUND: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. Howev...

Multiclassification Prediction of Enzymatic Reactions for Oxidoreductases and Hydrolases Using Reaction Fingerprints and Machine Learning Methods.

Journal of chemical information and modeling
Drug metabolism is a complex procedure in the human body, including a series of enzymatically catalyzed reactions. However, it is costly and time consuming to investigate drug metabolism experimentally; computational methods are hence developed to pr...