Questions tagged [deep-learning]
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How many protein sequences do we usually have for each species?
My question is exactly the one in the title. I add a particular example for more clarity. If I want to study the sequence of protein IkBα, do I find only one sequence or is there a database that ...
Gene rank scores from LINCS database: Evangelista et al. 2022
The website https://maayanlab.cloud/sigcom-lincs/#/SignatureSearch/UpDown can be used to "Identify reversers and mimickers from over 1 million signatures by entering up and down gene sets .. &...
What options should I explore to improve the output of the protein reconstruction?
We developed a neural network-based protein reconstruction tool to reconstruct the main chain from only CA atoms. we generated data from some selected PDBs from the RCSB website to train an NN model. ...
Why can't AlphaFold predict the consequences of point-mutations?
In the literature, it specifically states that AlphaFold has "Has not been trained to predict structural consequences of point mutations". See : https://alphafold.com/faq AlphaFold has not ...
How can I convert protein distance maps and sequences to a pdb files?
How can I convert protein distance maps and sequences to pdb files? For the same problem, in the case of a model predicting the structure of a protein, such as AlphaFold, how do we convert the ...
Transfer learning for a Convolutional NN for Recursion dataset
As a practice data analysis I am trying to train a convolutional neural network (CNN) on some cellular images made publicly available on Kaggle in 2019 by the company Recursion via supervised deep ...
Reproducible PyTorch Model
I'm using PyTorch (1.7.1), PyTorch Geometric (1.6.3), NVIDIA Cuda (11.2). I need to make a neural network reproducible for a competition. However, when I try: ...
Build protein-protein interaction prediction deep learning model
I'm an undergraduate biology student and my thesis is on designing a deep learning architecture to predict whether two proteins interact or not given their primary sequences. I have read some papers ...
Important genes beyond PAM50 for breast cancer classification
Note: this question has also been asked on Biostars I am currently trying to complete a Breast Cancer Classification task using Neural Networks. I have experimented with using my full dataset of gene ...
how to get access to genotypes and phenotypes used for a GWAS
I'm a master's student working on genomic prediction of complex traits using deep learning. i'm looking for a dataset of human genotypes and phenotypes that has been used for a GWAS. The only thing i ...
Calling variants with DeepVariant on targeted NGS sequencing (custom library)
I am seeking advice regarding DeepVariant analysis. To avoid false positives I'm using several variant callers and then the resulting common set will be considered as TP variants. One of the callers ...
What datasets are available out there for prediction based on DNA sequences? [closed]
I am looking for publicly available data for a genomics deep learning project. My goal is to compare different architectures to predict biological insights from DNA sequences. I have heard about ...
How to predict with the pre-trained DNABERT model?
I was curious to give DNA BERT a try. This is a BERT (Bidirectional Encoder Representations from Transformers) model that was trained on short (k=3,4,5, or 6) k-...
Metapath2vec on Drug-ADR Heterogeneous Graph
I am new in this field and I am having some problems regarding a new project. I built a graph using Drugbank Data connected to SIDER Adverse Reactions. I used Organ- level Terms to classify the ADRs ...
How does DeepVariant construct RGB images from DNA sequences?
DeepVariant is a pipeline to call genetic variants from DNA sequencing data. A major step, before feeding the CNN, is to translate these DNA sequences into images. It's unclear why and how Google ...