AIMC Topic: Mammals
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Hierarchical motor control in mammals and machines.
Nature communications
Dec 2, 2019
Advances in artificial intelligence are stimulating interest in neuroscience. However, most attention is given to discrete tasks with simple action spaces, such as board games and classic video games. Less discussed in neuroscience are parallel advan...
Multi-task learning improves ancestral state reconstruction.
Theoretical population biology
Jan 11, 2019
We consider the ancestral state reconstruction problem where we need to infer phenotypes of ancestors using observations from present-day species. For this problem, we propose a multi-task learning method that uses regularized maximum likelihood to e...
Optimal trajectory generation for time-to-contact based aerial robotic perching.
Bioinspiration & biomimetics
Nov 27, 2018
Many biological organisms (e.g. insects, birds, and mammals) rely on the perception of an informational variable called time-to-contact (TTC) to control their motion for various tasks such as avoiding obstacles, landing, or interception. TTC, defined...
A universal SNP and small-indel variant caller using deep neural networks.
Nature biotechnology
Sep 24, 2018
Despite rapid advances in sequencing technologies, accurately calling genetic variants present in an individual genome from billions of short, errorful sequence reads remains challenging. Here we show that a deep convolutional neural network can call...
Sensory cortex is optimized for prediction of future input.
eLife
Jun 18, 2018
Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimized to represent features in the recent sensory pas...
Preconditioning 2D Integer Data for Fast Convex Hull Computations.
PloS one
Mar 3, 2016
In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ≤ n, which also contains the same hull. We present an algorithm to precondition 2D da...
Mechanistic Model-Driven Biodesign in Mammalian Synthetic Biology.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2024
Mathematical modeling plays a vital role in mammalian synthetic biology by providing a framework to design and optimize design circuits and engineered bioprocesses, predict their behavior, and guide experimental design. Here, we review recent models ...
Improving flat fluorescence microscopy in scattering tissue through deep learning strategies.
Optics express
Jul 3, 2023
Intravital microscopy in small animals growingly contributes to the visualization of short- and long-term mammalian biological processes. Miniaturized fluorescence microscopy has revolutionized the observation of live animals' neural circuits. The te...
Profiling mechanisms that drive acute oral toxicity in mammals and its prediction via machine learning.
Toxicological sciences : an official journal of the Society of Toxicology
May 12, 2023
We present a mechanistic machine-learning quantitative structure-activity relationship (QSAR) model to predict mammalian acute oral toxicity. We trained our model using a rat acute toxicity database compiled by the US National Toxicology Program. We ...
Neuron tracing from light microscopy images: automation, deep learning and bench testing.
Bioinformatics (Oxford, England)
Dec 13, 2022
MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey pape...
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