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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.

BERT-Kcr is a tool for prediction of lysine crotonylation sites by a transfer learning method with pre-trained BERT models.

ProtTrans is providing state of the art pre-trained models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using various Transformers Models.

VIQoR, is a user-friendly web service for Visually supervised protein Inference and protein Quantification implemented in R. The Shiny web interface integrates the post-identification processes involved in protein inference and relative protein abundance summarization, along with smart and novel interactive visualization modules to support the common researchers with a straight-forward tool for protein quantification, data browsing and data inspection.

CoronaCentral is a tool for analyzing the vast coronavirus literature with CoronaCentral.

Biofactoid is a web-based system that empowers authors to capture and share machine-readable summaries of molecular-level interactions described in their publications.

COVID-19-CT-CXR is a public database of COVID-19 CXR and CT images, which are automatically extracted from COVID-19-relevant articles from the PubMed Central Open Access (PMC-OA) Subset.

WHOSe Heritage: Classification of UNESCO World Heritage "Outstanding Universal Value" Documents with Smoothed Labels This repository provides the supplemental materials for reproducing the results of the above-mentioned paper as submitted to arXiv preprint server, including both models and results.

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.

This is the place where you can find an updated list of the published mitochondrial sequences coming from the ancient DNA samples (aDNA). The main interest of our database lies in the anatomically modern Homo sapiens samples, ranging from the late Paleolithic to roughly Iron Age times, focusing on an Euroasian geographical area. We provide both the mtDNA sequences (in FASTA format), and the metadata for the samples (IDs, dates, geolocation, site, culture, mtDNA haplogroup etc., available to download in a tab-delimited text file).