miRNA Text Mining in Abstracts
Add topic column to data frame
Keywords - animals.
Assign topics based on precalculated scores
Assign topics based on LDA model
Keywords - biomarkers.
Calculate animal model scores for abstracts
Calculate biomarker scores for abstracts
Calculate patients scores for abstracts
Calculate scores of a self-chosen topic
Combine data frames into one data frame
Combine miRNA vectors into one
Combine data frames containing stop words
Compare count of miRNA names between different topics
Compare log2-frequency count of miRNA names between two topics
Compare top count of unique miRNA names per topic
Compare count of terms associated with a miRNA name over various topic...
Compare log2-frequency count of terms associated with a miRNA name
Compare shared terms associated with a miRNA name
Compare terms uniquely associated with a miRNA name
Count miRNA names in a data frame
Count occurrence of miRNA names above threshold
Count SNPs in a data frame
Count targets in data frame
Extract miRNA names from abstracts in data frame
Extract miRNA names from string
Extract SNPs from abstracts in data frame
Fit LDA-model
Generate data frame containing stop words
Identify top miRNA names distinct for one topic compared to another to...
Identify miRNA names distinct for one vector compared to another vecto...
Get miRNA names from a data frame
Get PubMed-IDs of a data frame
Get top miRNA names in common between two topics of a data frame
Get miRNA names in common between two vectors
Get SNPs from a data frame
Indicate if a miRNA name is contained in an abstract
Indicate if a term is contained in abstracts
Add miRNA targets from miRTarBase version 8.0
Add miRNA targets from an xlsx-file to a data frame
Keywords - patients.
Plot terms associated with LDA-fitted topics
Plot count of most frequently mentioned miRNA names
Plot occurrence count of miRNA names over different thresholds
Plot development of miRNA name mentioning over time
Plot number of newly mentioned miRNA names/year
Plot count of top terms associated with a miRNA name
Plot perplexity score of various LDA models
Plot frequency of animal model scores in abstracts
Plot frequency of biomarker scores in abstracts
Plot frequency of patient scores in abstracts
Plot frequency of self-chosen topic scores in abstracts
Plot count of miRNA targets
Plot targets and corresponding miRNAs as a scatter plot
Create wordcloud of terms associated with a miRNA name
Convert PubMed-file from PubMed into a data frame
Convert JATS-file from PubMed into a data frame
Save data frame(s) as xlsx-file
Save the last generated figure
Subset data frame for a term
Subset data frame for specific miRNA names
Subset data frame for miRNA names exceeding a threshold
Subset data frame for abstracts of research articles
Subset data frame for abstracts of review articles
Subset data frame for specific SNPs
Subset data frame for abstracts published in a specific period
Providing tools for microRNA (miRNA) text mining. miRetrieve summarizes miRNA literature by extracting, counting, and analyzing miRNA names, thus aiming at gaining biological insights into a large amount of text within a short period of time. To do so, miRetrieve uses regular expressions to extract miRNAs and tokenization to identify meaningful miRNA associations. In addition, miRetrieve uses the latest miRTarBase version 8.0 (Hsi-Yuan Huang et al. (2020) "miRTarBase 2020: updates to the experimentally validated microRNA–target interaction database" <doi:10.1093/nar/gkz896>) to display field-specific miRNA-mRNA interactions. The most important functions are available as a Shiny web application under <https://miretrieve.shinyapps.io/miRetrieve/>.