notebook showing use of the trained models to produce Pfam class predictions as well as embeddings is available in GitHub athttps://colab.sandbox.google.com/github/google-research/google-research/blob/master/using_dl_to_annotate_protein_universe/Using_Deep_Learning_to_Annotate_the_Protein_Universe....
Deep embedding and alignment of protein sequences Article 15 December 2022 Using deep learning to annotate the protein universe Article 21 February 2022 Main Detecting protein sequence homology using sequence similarity is the standard approach to identifying evolutionarily conserved functions that are co...
We collect, annotate and visually parse images from potentially hazardous areas. We detect the flood conditions and identify objects in harm's way by stacking deep learning models such as a convolutional neural network (CNN), single-shot multi-box object detection (SSD). We then feed the image...
Localization (without tracking) can also be achieved with deep learning software likekeras-retinanet, theTensorflow Object Detection API, orMatterPort's Mask R-CNN. Check out our paperto find out more. How to use DeepPoseKit DeepPoseKit is designed for easy use. For example, training and saving...
(SOTA) deep learning algorithms. In this paper, we present a new interactive deep learning segmentation algorithm,ImPartial, that incorporates human feedback during the training phase to create optimal models for images with small/thin repeatable objects (cells, neurons, vessels, etc). Specifically,...
Nevertheless, we only had to annotate a subset of the videos (two of five recorded videos per dog) and frames per video (1 frame/s) to train the key point detectors, highlighting the efficiency of this method. Future research will reveal the extent to which the trained detectors can ...
Inspired by the deep learning breakthrough in image-based plant disease recognition, this work proposes deep learning models for image-based automatic diagnosis of plant disease severity. We further annotate the apple healthy and black rot images in the public PlantVillage dataset [3] with severity...
In an experimental setup of an active learning system, it is assumed that the quality of labeled data produced by human experts is always high. But in reality, this is not true for a couple of reasons such as: some instances are inheritably difficult to annotate by humans and even by mac...
Using deep learning to annotate the protein universe Article 21 February 2022 Current progress and open challenges for applying deep learning across the biosciences Article Open access 01 April 2022 Highly accurate protein structure prediction with AlphaFold Article Open access 15 July 2021 Introdu...
to predict EC numbers could substantially reduce the number of un-annotated genes. Here we present a deep learning model, DeepECtransformer, which utilizes transformer layers as a neural network architecture to predict EC numbers. Using the extensively studiedEscherichia coliK-12 MG1655 genome, Deep...