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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De novo antibody sequencing fromMS/MS Ion Trap proteomics raw signal
I've read about different proteomics tools that can do de novo assembly of MS/MS Ion Trap proteomics signatures for de novo antibody sequencing. Given the way CDR3s of antibodies are created, together ...
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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 ...
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How to extract and visualize sequence logos from CNN kernels?
I created a basic CNN architecture using Tensorflow to classify transcription factor binding sites. My aim is to somehow extract and visualize sequence logos from the convolutional kernels. The model ...
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Gene names from components in NMF analysis
I am using Rcppml package in R for my NMF analysis, I have a matrix from single-cell analysis. I have cells scores and I wanted to know how to extract genes instead of the components.
i used the ...
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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 ...
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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:
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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 ...
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Biological datasets for polythetic classification
Question: What are some instances of polythetic datasets in biology? In particular, I am looking for a dataset to benchmark a machine learning algorithm optimized via episodic training.
On polythetic ...
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Challenging benchmarks for supervised learning on sparse scRNA-seq data
One challenging aspect of modeling scRNA-seq data is data sparsity, that is, scRNA-seq measurements typically suffer from large fractions of observed zeros (i.e. dropouts), where a given gene in a ...
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Extract features from fasta sequences and train the classifier
I am new to the bioinformatics field. I have positive and negative protein sequences for acetylation PTM. Now, I want to train a classifier, say SVM. What will be the next step? How can I convert ...
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Books on application of Machine Learning in Bioinformatics
I'm looking for books on applications of machine learning and statistical data mining in bioinformatics with example codes provided in R and/or python.
I came across the following two books: the first ...
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how to train a gene dataset with a nearest shrunken centroid classifier?
I have a data file named "geneexp.csv".
the data contains information about gene expression of three different cell types (CD4 and CD8, CD19) I want to classify cells by performing the ...
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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 ...
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Any suggestions for cultivar identification using SSR (simple sequence repeat) markers
This is the data I have now: 30 simple sequence repeat (SSR) markers for 80 cultivars of cucumber. 10 of the 80 cultivars belong to one cultivar (let's say A).
My goal is to classify an unknown ...
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Problems replicating Kover paper results
I am trying to replicate the results for the creator of this repo: https://github.com/aldro61/kover2_paper for genotype to phenotype machine learning interpretable (decision tree) prediction.
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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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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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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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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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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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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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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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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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How are the scores of GeneSplicer, MaxEntScan and SpliceRegion interpreted from VEP annotations?
I am using VEP from Ensembl to annotate my VCF files with the extra plugins of GeneSplicer, MaxEntScan and SpliceRegion. However, I don't fully understand the output of these scores.
I know that they ...
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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 to perform classification.
There are some normal ...
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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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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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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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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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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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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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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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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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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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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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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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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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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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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. The accuracy of the model is 0.73 ...
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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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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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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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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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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 ...
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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 ...
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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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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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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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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 ...
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