LBDiscover0.1.0 package

Literature-Based Discovery Tools for Biomedical Research

abc_model_opt

Optimize ABC model calculations for large matrices

abc_model_sig

Apply the ABC model with statistical significance testing

abc_model

Apply the ABC model for literature-based discovery with improved filte...

abc_timeslice

Apply time-sliced ABC model for validation

add_statistical_significance

Add statistical significance testing based on hypergeometric tests

alternative_validation

Alternative validation for large matrices

anc_model

ANC model for literature-based discovery with biomedical term filterin...

apply_bitola_flexible

Apply a flexible BITOLA-style discovery model without strict type cons...

apply_correction

Apply correction to p-values

authenticate_umls

Authenticate with UMLS

bitola_model

Apply BITOLA-style discovery model

calc_bibliometrics

Calculate basic bibliometric statistics

calc_doc_sim

Calculate document similarity using TF-IDF and cosine similarity

calculate_score

Calculate ABC score based on specified method

clear_pubmed_cache

Clear PubMed cache

cluster_docs

Cluster documents using K-means

compare_terms

Compare term frequencies between two corpora

create_citation_net

Create a citation network from article data

create_comat

Create co-occurrence matrix without explicit entity type constraints

create_dummy_dictionary

Helper function to create dummy dictionaries

create_report

Generate a comprehensive discovery report

create_sparse_comat

Create a sparse co-occurrence matrix

create_tdm

Create a term-document matrix from preprocessed text

create_term_document_matrix

Create a term-document matrix from preprocessed text

detect_lang

Detect language of text

diversify_abc

Enforce diversity in ABC model results

diversify_b_terms

Enforce diversity by selecting top connections from each B term

diversify_c_paths

Enforce diversity for C term paths

dot-dict_cache_env

Environment to store dictionary cache data

dot-pubmed_cache_env

Environment to store PubMed cache data

enhance_abc_kb

Enhance ABC results with external knowledge

eval_evidence

Evaluate literature support for discovery results

export_chord_diagram

Export interactive HTML chord diagram for ABC connections

export_chord

Export interactive HTML chord diagram for ABC connections

export_network

Export ABC results to simple HTML network

extract_entities_workflow

Extract entities from text with improved efficiency using only base R

extract_entities

Extract and classify entities from text with multi-domain types

extract_mesh_from_text

Extract MeSH terms from text format instead of XML

extract_ner

Perform named entity recognition on text

extract_ngrams

Extract n-grams from text

extract_terms

Extract common terms from a corpus

extract_topics

Apply topic modeling to a corpus

fetch_and_parse_gene

Fetch and parse Gene data

fetch_and_parse_pmc

Fetch and parse PMC data

fetch_and_parse_protein

Fetch and parse Protein data

fetch_and_parse_pubmed

Fetch and parse PubMed data

filter_by_type

Filter a co-occurrence matrix by entity type

find_abc_all

Find all potential ABC connections

find_similar_docs

Find similar documents for a given document

find_term

Find primary term in co-occurrence matrix

gen_report

Generate comprehensive discovery report

get_dict_cache

Get dictionary cache environment

get_pmc_fulltext

Retrieve full text from PubMed Central

get_pubmed_cache

Get the pubmed cache environment

get_service_ticket

Get a service ticket from a TGT URL

get_term_vars

Extract term variations from text corpus

get_type_dist

Get entity type distribution from co-occurrence matrix

get_umls_semantic_types

Get UMLS semantic types for a given dictionary type

is_valid_biomedical_entity

Determine if a term is likely a specific biomedical entity with improv...

list_to_df

Convert a list of articles to a data frame

load_dictionary

Load biomedical dictionaries with improved error handling

load_from_mesh

Load terms from MeSH using rentrez with improved error handling

load_from_umls

Load terms from UMLS API

load_mesh_terms_from_pubmed

Load terms from MeSH using PubMed search

load_results

Load saved results from a file

lsi_model

LSI model with enhanced biomedical term filtering and NLP verification

map_ontology

Map terms to biomedical ontologies

merge_entities

Combine and deduplicate entity datasets

merge_results

Merge multiple search results

min_results

Ensure minimum results for visualization

ncbi_search

Search NCBI databases for articles or data

null_coalesce

Null coalescing operator

parallel_analysis

Apply parallel processing for document analysis

parse_pubmed_xml

Parse PubMed XML data with optimized memory usage

perm_test_abc

Perform randomization test for ABC model

plot_heatmap

Create heatmap visualization from results

plot_network

Create network visualization from results

prep_articles

Prepare articles for report generation

preprocess_text

Preprocess article text

process_mesh_chunks

Process MeSH data in chunks to avoid memory issues

process_mesh_xml

Process MeSH XML data with improved error handling

pubmed_search

Search PubMed for articles with optimized performance

query_external_api

Query external biomedical APIs to validate entity types

query_mesh

Query for MeSH terms using E-utilities

query_umls

Query UMLS for term information

remove_ac_terms

Remove A and C terms that appear as B terms

retry_api_call

Retry an API call with exponential backoff

run_lbd

Perform comprehensive literature-based discovery without type constrai...

safe_diversify

Diversify ABC results with error handling

sanitize_dictionary

Enhanced sanitize dictionary function

save_results

Save search results to a file

segment_sentences

Perform sentence segmentation on text

shadowtext

Helper function to draw text with a shadow/background

standard_validation

Standard validation method using hypergeometric tests

valid_entities

Filter entities to include only valid biomedical terms

validate_abc

Apply statistical validation to ABC model results with support for lar...

validate_biomedical_entity

Validate biomedical entities using BioBERT or other ML models

validate_entity_comprehensive

Comprehensive entity validation using multiple techniques

validate_entity_with_nlp

Validate entity types using NLP-based entity recognition with improved...

validate_umls_key

Validate a UMLS API key

vec_preprocess

Vectorized preprocessing of text

vis_abc_heatmap

Create a heatmap of ABC connections

vis_heatmap

Create an enhanced heatmap of ABC connections

vis_network

Create an enhanced network visualization of ABC connections

visualize_abc_network

Visualize ABC model results as a network

A suite of tools for literature-based discovery in biomedical research. Provides functions for retrieving scientific articles from 'PubMed' and other NCBI databases, extracting biomedical entities (diseases, drugs, genes, etc.), building co-occurrence networks, and applying various discovery models including 'ABC', 'AnC', 'LSI', and 'BITOLA'. The package also includes visualization tools for exploring discovered connections.

  • Maintainer: Chao Liu
  • License: GPL-3
  • Last published: 2025-06-16