AIMC Topic: Software

Clear Filters Showing 3401 to 3410 of 3675 articles

Machine Learning in Untargeted Metabolomics Experiments.

Methods in molecular biology (Clifton, N.J.)
Machine learning is a form of artificial intelligence (AI) that provides computers with the ability to learn generally without being explicitly programmed. Machine learning refers to the ability of computer programs to adapt when exposed to new data....

Noise peak filtering in multi-dimensional NMR spectra using convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Multi-dimensional NMR spectra are generally used for NMR signal assignment and structure analysis. There are several programs that can achieve highly automated NMR signal assignments and structure analysis. On the other hand, NMR spectra ...

SpliceRover: interpretable convolutional neural networks for improved splice site prediction.

Bioinformatics (Oxford, England)
MOTIVATION: During the last decade, improvements in high-throughput sequencing have generated a wealth of genomic data. Functionally interpreting these sequences and finding the biological signals that are hallmarks of gene function and regulation is...

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play.

Science (New York, N.Y.)
The game of chess is the longest-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that ha...

Transfer learning for biomedical named entity recognition with neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/protei...

Hercules: a profile HMM-based hybrid error correction algorithm for long reads.

Nucleic acids research
Choosing whether to use second or third generation sequencing platforms can lead to trade-offs between accuracy and read length. Several types of studies require long and accurate reads. In such cases researchers often combine both technologies and t...

EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery.

Bioinformatics (Oxford, England)
MOTIVATION: Biclustering algorithms are commonly used for gene expression data analysis. However, accurate identification of meaningful structures is very challenging and state-of-the-art methods are incapable of discovering with high accuracy differ...

YAMDA: thousandfold speedup of EM-based motif discovery using deep learning libraries and GPU.

Bioinformatics (Oxford, England)
MOTIVATION: Motif discovery in large biopolymer sequence datasets can be computationally demanding, presenting significant challenges for discovery in omics research. MEME, arguably one of the most popular motif discovery software, takes quadratic ti...

Attractor dynamics of a Boolean model of a brain circuit controlled by multiple parameters.

Chaos (Woodbury, N.Y.)
Studies of Boolean recurrent neural networks are briefly introduced with an emphasis on the attractor dynamics determined by the sequence of distinct attractors observed in the limit cycles. We apply this framework to a simplified model of the basal ...