Questions tagged [machine-learning]
A subset of articial intelligence methods which 'learn' through training on real-world data sets. The model is then tested on a 'test' data set and initially assessed through an accuracy measure. The approach is specifically termed 'supervised learning'.
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How to infer the number of chaperones involved in protein folding?
Let us suppose to have the complete CDS set of an organisms. Let us suppose to want to infer the number of chaperones involved in folding a certain subclass of proteins in this data set.Is there any ...
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2answers
70 views
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 ...
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1answer
20 views
Is it possible to predict protein-ligand binding kinetics using machine learning? [closed]
I would like to work on a project that involves the prediction of protein-ligand binding kinetics. What might be the feature that is relevant for the prediction?
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1answer
46 views
What are the state-of-the-art cell-type RNA-Seq deconvolution methods?
I would like to find the proportion of each cell-type in bulk RNA-Seq transcriptomics data. I am looking for some guidance on the following:
What are the state-of-the-art methods?
What are their ...
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1answer
42 views
How do I set a neural network to loop multiple times and average the resulting values?
I have a script in R/RStudio which creates random datasets of binomial variables, feeds them through a neural network, and calculates their likelihood ratio statistic and deviance. I'd like the script ...
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26 views
Available Protein sequence alignment dataset and HMM model
It may better to move the question here.
I am new to biology and I find my algorithm may be used in the Protein sequence alignment, since it is a henced HMM model. I find that people use HMM to ...
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1answer
43 views
Generate ligands candidates based on protein shape
Recent approaches to novel drug design using machine learning (ML) and deep learning, often involve generating hundreds of potential ligands which are later tested by docking with a target protein and ...
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1answer
66 views
Problem with classification model of genomic data: every machine learing model predicts wrongly almost always the same subset of dataset
First of all, I'd like to apologize for any spelling or grammar mistakes.
I'm having a problem using R for a classification problem. My dataset contains ~300.000 genomic data, and the features are ...
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2answers
329 views
BERT Language Model and Gene Sequences - How Do I Relate Clusters of Sequences?
I hope you'll indulge a question from a computer scientist with limited bioinformatics knowledge. I've been working with the Google tool for language modeling called BERT. It's generally regarded ...
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Portals besides the National Cancer Institute GDC Data Portal for downloading histology slides
I am downloading sample slides (in svs format) from the GDC Portal for a convolutional neural network model, but I also need normal tissue slides. There are some normal tissue slides that are adjacent ...
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1answer
22 views
Feature extraction methods that can handle inconsistent numbers of atoms for molecular dynamics
I want to compare the protein dynamics
) pH 7 versus pH 3, or
) wild type versus mutant
The protein will have slightly different number of atoms at each condition, due to protonation or mutation, ...
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1answer
20 views
Why my bim file doesn't match to my ped file as the Plink documentation suggests?
Plink documentation about .bim says the columns 5 and 6 are the Allele 1 and Allele 2 respectively.
The documentation about the .ped in turn, says "...The first six fields are the same as those in a ....
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1answer
48 views
Use of Electronic Phenotype in EHR
May I know what's the use of Electronic Phenotyping using EHR data?
I did refer this link but have few questions
I understand that ...
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2answers
48 views
What is the significance of enrichment factor regarding machine learning methods?
I'm fairly new to the field of bioinformatics and ran into a question while reading a paper I found on bioRxiv. The overall setting of the paper is using multi-task deep neural networks for kinase ...
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2answers
75 views
What kind of analysis is practically done on GSE data files?
I have a GSE data file in csv file format containing fields such as: ID, adj.P.Val, P.Value, t, B, logFC, Gene.symbol, Gene.title. In which adj.P.Val, P.Value, t, B, logFC fields being numeric. What ...
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3answers
137 views
16S species-level taxonomic assignment--what is the current state of the art?
We currently use DADA2 for picking ASVs and the assignTaxonomy funciton for assingment to genera. Google does bring up various recent articles on species-level ...
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73 views
length of 'dimnames' [1686] must match that of 'dims' [3]
Please if anyone has experience with the use of the BSEQ-SC package for the deconvolution of bulk RNA sequencing data with single cell RNA sequencing data I will be very grateful for your suggestion.
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Error using bseqsc
I will be very grateful for any hint on how to overcome the error. I wish to deconvolve my bulk RNA seq data obtained from the lungs of mice using single cell RNA seq data. For practice, I am ...
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1answer
52 views
How to predict protein binding to ligands?
I want to predict from protein sequence if the protein binds to metal, nuclear or small ligand. How can I do this ? Which features are relevant if I want to use them in a machine learning algorithm ?
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3answers
244 views
Deep learning RNA sequences
Currently I'm working on a project, which combines deep learning with RNA sequences. I'll try to predict pseudotorsion angles [1] from raw rna sequence. The ideas is to train a neural network with raw ...
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0answers
45 views
Is the visual cortex of a newborn baby immediately capable of object detection or is this skill learned over time, and if so, how? [closed]
Is the visual cortex of newborn babies right off the bat capable of making sense of raw visual data, for instance, converting the constant stream of raw RGB images perceived by the eyes into a ...
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1answer
54 views
Finding the members in a confusion matrix
I have inferred a confusion matrix of training and test set by neural network. I want to know which members are in the confusion matrix.
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1answer
90 views
Recommendation for a binary dataset for Computational Biology open access (as in a dataset with 1 and 0 that can be used to apply ML techniques? [closed]
I have a couple of modified ML methods that I want to test with biological binary data - specifically binary gene expression data - e.g. https://eprints.soton.ac.uk/69359/1/Thesis.pdf that might ...
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2answers
34 views
General framework for fusing biological networks
I know that there are different types of biological networks. Protein-protein interaction, gene interaction, metabolic networks, gene expression networks, etc. Each of these networks can be ...
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1answer
85 views
How I know which gene is a good predictor in this neural network or not?
I have 25 highly differentially expressed genes among and patients to chemotherapy.
I have made a neural network of these genes. Accuracy of model is 0.73 but I don't know from 25 genes how I could ...
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1answer
53 views
De novo motif discovery in protein sequences
I am trying to build a features matrix to be used for Random Forest based classification. I'd like to add, as features, short motifs which are common to all the protein sequences belonging to a ...
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1answer
124 views
Question about research in bioinformatics for Computer Science student [closed]
I am a computer science student, who was interested in taking research in the field of bioinformatics.
The first research idea I had was to make a model that could predict the possibility of type 2 ...
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1answer
867 views
Integrative analysis of omics studies using machine learning
I would like to use public omics datasets (ChIP-seq, RNA-seq, and ATAC-seq) from different studies to do an integrative analysis as follow:
Normalise samples, within each type of omics, from ...
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1answer
158 views
Machine learning using protein-sequences
I'm participating in a bioinformatics machine-learning seminar at my university. The main task is predicting binary classification of protein-protein interactions using sequence data as input.
One ...
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1answer
85 views
Link Prediction in Bipartite Networks between biological pathways and drugs
Currently I'm building a big matrix (using microarray, mass spectrometry, RNAseq data) that consist by pathways (rows) and treatment/drugs (columns).
The values of that matrix are scores that ...
2
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1answer
47 views
Proteins that cannot form biofilm?
I am trying to build a machine learning training set for bacterial protein sequences that form biofilm, and that cannot. I collected the positive sequences from the GO ontology website but for ...
2
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0answers
441 views
How to prevent sklearn Imputer(missing_values=“NaN”, strategy=“mean”, axis=0).fit_transform(data) from removing columns with only NA in them [closed]
I am trying to test a preexisting python machine learning script with a subset of my genetic data. One of the feature columns I am using happens to only have NA values in it. I lose this column when ...
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1answer
154 views
Preparing binary matrix data for Scikit classification algorithms
I made this post in regular stack overflow but I was told about this awesome feature by @nbryans.
I am a researcher (my programming knowledge is small) conducting analysis on a set of antibiotic (...
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2answers
280 views
Rule Extraction from nnet results
I used a script in R language that uses nnet library to predict promoter bacteria and i would like to know how to extract rules from this neural network results.
As my input of the neural network i ...
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2answers
107 views
How can I use annotations to remove variants not relevant to cancer risk?
I currently have ~180 whole germlines and around 10M SNPs/indels. I would like to build a predictive model using Machine Learning (ML) techniques to predict cancer risk according to these germline ...
