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Web-based application that provides computer-annotated biomedical concepts, such as genes and mutations, in PubMed citations and PMC full-text articles.

Restructured version of Gene Expression Omnibus (GEO) that provides a user friendly interface for curating GEO database

BioVAE is a pre-trained latent variable language model for biomedical text mining. Large scale pre-trained language models (PLMs) have advanced state-of-the-art (SOTA) performance on various biomedical text mining tasks. The power of such PLMs can be combined with the advantages of deep generative models. These are examples of these combinations. However, they are trained only on general domain text, and biomedical models are still missing. In this work, we describe BioVAE, the first large scale pre-trained latent variable language model for the biomedical domain, which uses the OPTIMUS framework to train on large volumes of biomedical text. The model shows SOTA performance on several biomedical text mining tasks when compared to existing publicly available biomedical PLMs.

Ontology-based systematic representation and analysis of drug adverse events and its usage in study of adverse events given different patient age and disease conditions.

TISSUES is a weekly updated web resource that integrates evidence on tissue expression from manually curated literature, proteomics and transcriptomics screens, and automatic text mining. We map all evidence to common protein identifiers and Brenda Tissue Ontology terms, and further unify it by assigning confidence scores that facilitate comparison of the different types and sources of evidence. We finally visualize these scores on a schematic human body to provide a convenient overview.

A web based framework that takes advantage of domain specific ontologies, and Natural Language Processing, aiming to empower exploration of biomedical resources via semantic-based querying and search. The NLP engine analyzes the input free-text query and translates it into targeted queries with terms from the underlying ontology. Each query is passed to the semantically-annotated tools repository, and based on similarity matches, it ranks the available resources.

Helps human reviewers interpret the clinical significance of variants. InterVar can take a pre-annotated or VCF file as input and generate automated interpretation on 18 criteria.

A computational framework for the non-specialist to profile cellular heterogeneity in cytometry datasets. The immunoCluster package uses the scDataViz bioconductor package’s vizualization tools and adaptation of the SingleCellExperiment data structure to build simple and flexible cytometry analysis workflows like those outlined in Nowicka et al. (2017) CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets.

Creates high-quality 3D/4D animations using a natural-language based syntax.

Package that facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches.