AIMC Topic: Machine Learning

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iTIS-PseKNC: Identification of Translation Initiation Site in human genes using pseudo k-tuple nucleotides composition.

Computers in biology and medicine
Translation is an essential genetic process for understanding the mechanism of gene expression. Due to the large number of protein sequences generated in the post-genomic era, conventional methods are unable to identify Translation Initiation Site (T...

Implicit Value Updating Explains Transitive Inference Performance: The Betasort Model.

PLoS computational biology
Transitive inference (the ability to infer that B > D given that B > C and C > D) is a widespread characteristic of serial learning, observed in dozens of species. Despite these robust behavioral effects, reinforcement learning models reliant on rewa...

A Tool for Predicting Regulatory Approval After Phase II Testing of New Oncology Compounds.

Clinical pharmacology and therapeutics
We developed an algorithm (ANDI) for predicting regulatory marketing approval for new cancer drugs after phase II testing has been conducted, with the objective of providing a tool to improve drug portfolio decision-making. We examined 98 oncology dr...

The foundations of the human cultural niche.

Nature communications
Technological innovations have allowed humans to settle in habitats for which they are poorly suited biologically. However, our understanding of how humans produce complex technologies is limited. We used a computer-based experiment, involving humans...

Analyzing animal behavior via classifying each video frame using convolutional neural networks.

Scientific reports
High-throughput analysis of animal behavior requires software to analyze videos. Such software analyzes each frame individually, detecting animals' body parts. But the image analysis rarely attempts to recognize "behavioral states"-e.g., actions or f...

RBoost: Label Noise-Robust Boosting Algorithm Based on a Nonconvex Loss Function and the Numerically Stable Base Learners.

IEEE transactions on neural networks and learning systems
AdaBoost has attracted much attention in the machine learning community because of its excellent performance in combining weak classifiers into strong classifiers. However, AdaBoost tends to overfit to the noisy data in many applications. Accordingly...

Searching molecular structure databases with tandem mass spectra using CSI:FingerID.

Proceedings of the National Academy of Sciences of the United States of America
Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. ...

The Large Scale Machine Learning in an Artificial Society: Prediction of the Ebola Outbreak in Beijing.

Computational intelligence and neuroscience
Ebola virus disease (EVD) distinguishes its feature as high infectivity and mortality. Thus, it is urgent for governments to draw up emergency plans against Ebola. However, it is hard to predict the possible epidemic situations in practice. Luckily, ...

Exploring the forest instead of the trees: An innovative method for defining obesogenic and obesoprotective environments.

Health & place
Past research has assessed the association of single community characteristics with obesity, ignoring the spatial co-occurrence of multiple community-level risk factors. We used conditional random forests (CRF), a non-parametric machine learning appr...

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

IEEE transactions on cybernetics
Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this pap...