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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Are there applications of semi-supervised learning to genomics?
Semi-supervised learning is when a portion of the training data set is labeled, and the rest is unlabeled; the unlabeled data is used to improved learning performance / accuracy.
Are there (i.e., have ...
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Intepreting and applying ordinal logistic regression coefficients to calculate probabilities?
Can someone help hint me how I can interpret ordinal logistic regression coefficients and how I can use the .L, .Q and .C terms to calculate probabilities? I am analysing a dataset, where people ...
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Is a classification tree appropriate method to use for my project?
I have about ~3000 genomes of organisms and presence (recorded as 1)/absence (recorded as 0) data of ~300 genes in them. Among 3000 genomes, we have experimental data on 20 organisms, which were ...
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Model optimization causes overfitting
I'm working on an ML model to predict colorectal cancer using data from the human microbiome (collected from fecal samples).
My dataset is made up of metadata (containing phenotypic information on the ...
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Feature-selection microbiome data to build a model to predict cancer
I want to build a machine learning model to predict colorectal cancer based on 16S rRNA microbiome data (stool samples).
I have filtered the data using filtering approach by Duvallet(removing samples ...
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How evaluate biclustering algorithm over real datasets containing labels?
I have a set of real data containing labels. However, in some biclustering algorithms (e.g., Cheng and Church Algorithm), originally authors applied gene expression data like Yeast without having ...
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Applying glmnet to identify predictors for subtypes
I am new to glmnet and other ML techniques, so apologise in advance if this sounds a trivial question. However, your guidance is very much appreciated.
So, I have nearly 700 genes with their ...
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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 .. &...
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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.
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Is current AI able to generate RNA sequences of viruses? [closed]
After seeing a video of a combination of CRISPR and AI, and an article of someone who made two babies immune against HIV and still healthy, I wondered about something. If such complicated thing, to ...
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Multivariate analysis of cell culture bioprocess
I am seeking statistical support for the following bacterial growth time series.
In the lab, we have cell cultures growing in bioreactors. Every day we measure the concentration in mmol-1 of a set of ...
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Reduce Overfit by removing insignificant proteins through PSEA analysis
I'm training a ML model for disease prediction using protein composition as input, but overfit is present. While looking to remove proteins and reduce multi-correlation, as remove composition ...
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Advise on building an effect ML model for predicting important proteins for drug response
I want to create a model to predict proteins which could be associated with drug response in cancer cell lines. I have cell line proteomics data, with compound screening data they have gained for a ...
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How to identify genomic regions / peaks associated with enhancers (TF binding sites)? Is there a tool or a formal recipe?
I am attempting to identify DNA sequences/regions associated with enhancers in my NGS sequencing data. How can I identify (from peak files/counts for chip-seq, atac etc.) genomics regions/peaks ...
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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
This question was also asked on Biostars
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 ...
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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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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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