AIMC Topic: Mice

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Mantis-ml: Disease-Agnostic Gene Prioritization from High-Throughput Genomic Screens by Stochastic Semi-supervised Learning.

American journal of human genetics
Access to large-scale genomics datasets has increased the utility of hypothesis-free genome-wide analyses. However, gene signals are often insufficiently powered to reach experiment-wide significance, triggering a process of laborious triaging of gen...

SANPolyA: a deep learning method for identifying Poly(A) signals.

Bioinformatics (Oxford, England)
MOTIVATION: Polyadenylation plays a regulatory role in transcription. The recognition of polyadenylation signal (PAS) motif sequence is an important step in polyadenylation. In the past few years, some statistical machine learning-based and deep lear...

Uncovering tissue-specific binding features from differential deep learning.

Nucleic acids research
Transcription factors (TFs) can bind DNA in a cooperative manner, enabling a mutual increase in occupancy. Through this type of interaction, alternative binding sites can be preferentially bound in different tissues to regulate tissue-specific expres...

A reference library for assigning protein subcellular localizations by image-based machine learning.

The Journal of cell biology
Confocal micrographs of EGFP fusion proteins localized at key cell organelles in murine and human cells were acquired for use as subcellular localization landmarks. For each of the respective 789,011 and 523,319 optically validated cell images, morph...

MRI-Based Deep Learning Segmentation and Radiomics of Sarcoma in Mice.

Tomography (Ann Arbor, Mich.)
Small-animal imaging is an essential tool that provides noninvasive, longitudinal insight into novel cancer therapies. However, considerable variability in image analysis techniques can lead to inconsistent results. We have developed quantitative ima...

OncoMX: A Knowledgebase for Exploring Cancer Biomarkers in the Context of Related Cancer and Healthy Data.

JCO clinical cancer informatics
PURPOSE: The purpose of OncoMX knowledgebase development was to integrate cancer biomarker and relevant data types into a meta-portal, enabling the research of cancer biomarkers side by side with other pertinent multidimensional data types.

A Deep Learning Approach to Antibiotic Discovery.

Cell
Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed pr...

Evaluation of genotoxicity after acute and chronic exposure to 2,4-dichlorophenoxyacetic acid herbicide (2,4-D) in rodents using machine learning algorithms.

The Journal of toxicological sciences
2,4-Dichlorophenoxyacetic acid (2,4-D) is one of the most widely used herbicides in the world, but its mutagenic and carcinogenic potential is still controversial. We simulated environmental exposure to 2,4-D, with the objective of evaluating the gen...

Machine learning-based automated phenotyping of inflammatory nocifensive behavior in mice.

Molecular pain
The discovery and development of new and potentially nonaddictive pain therapeutics requires rapid, yet clinically relevant assays of nociception in preclinical models. A reliable and scalable automated scoring system for nocifensive behavior of mice...