Biology subjects

Orlic-Milacic, M.

Publications and source records attributed to Orlic-Milacic, M..

4 recordsLinked to original sources

bioRxiv2025

React-to-Me: A Conversational Interface for Interactive Exploration of the Reactome Pathway Knowledgebase.

The Reactome Pathway Knowledgebase (www.reactome.org) provides expert-curated information on human biological pathways, molecular interactions, and disease mechanisms. However, its complex data model and keyword-based search interface present accessibility barriers for non-expert users. In contrast, general-purpose conversational AI systems offer intuitive natural language interfaces but lack the domain-specificity, transparent sourcing, and factual reliability required for scientific applications. To address this gap, we developed React-to-Me (https://reactome.org/chat), a domain-specific conversational assistant that enables users to query Reactome using natural language while maintaining scientific rigor and source traceability. React-to-Me integrates hybrid retrieval-augmented generation (RAG) with constrained language model generation to ensure that all responses are grounded in curated Reactome content and directly linked to corresponding knowledgebase entries. When internal coverage is insufficient, the system defers to trusted external biomedical sources rather than generating speculative or unverified content. Computational benchmarking confirmed that combining semantic vector search with keyword-based matching substantially improved contextual grounding and factual precision relative to dense-only retrieval baselines. In blinded expert evaluations, grounded responses were more likely to receive higher quality ratings than ungrounded counterparts, with significant gains in factual accuracy, biological specificity, and mechanistic depth. User surveys further indicated strong satisfaction with ease of use, citation reliability, and factual accuracy. These findings demonstrate that domain-specific grounding can markedly improve the reliability and usability of conversational AI for biological knowledge exploration. React-to-Me provides a transparent and scientifically robust interface for accessing and exploring Reactome content and is freely available at https://reactome.org/chat. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/693752v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1ef0d73org.highwire.dtl.DTLVardef@15c2d4dorg.highwire.dtl.DTLVardef@a2338corg.highwire.dtl.DTLVardef@e639fd_HPS_FORMAT_FIGEXP M_FIG C_FIG

scientific communication and education↗

bioRxiv2023

ChatGPT usage in the Reactome curation process

Appreciating the rapid advancement and ubiquity of generative AI, particularly ChatGPT, a chatbot using large language models like GPT, we endeavour to explore the potential application of ChatGPT in the data collection and annotation stages within the Reactome curation process. This exploration aimed to create an automated or semi-automated framework to mitigate the extensive manual effort traditionally required for gathering and annotating information pertaining to biological pathways, adopting a Reactome "reaction-centric" approach. In this pilot study, we used ChatGPT/GPT4 to address gaps in the pathway annotation and enrichment in parallel with the conventional manual curation process. This approach facilitated a comparative analysis, where we assessed the outputs generated by ChatGPT against manually extracted information. The primary objective of this comparison was to ascertain the efficiency of integrating ChatGPT or other large language models into the Reactome curation workflow and helping plan our annotation pipeline, ultimately improving our protein-to-pathway association in a reliable and automated or semi-automated way. In the process, we identified some promising capabilities and inherent challenges associated with the utilisation of ChatGPT/GPT4 in general and also specifically in the context of Reactome curation processes. We describe approaches and tools for refining the output given by ChatGPT/GPT4 that aid in generating more accurate and detailed output.

molecular biology↗

bioRxiv2023

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Disease variant annotation in the context of biological reactions and pathways can provide a standardized overview of molecular phenotypes of pathogenic mutations that is amenable to computational mining and mathematical modeling. Reactome, an open source, manually curated, peer-reviewed database of human biological pathways, provides annotations for over 4000 disease variants of close to 400 genes in the context of [~]800 disease reactions constituting [~]400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics (ACMG). Reactomes pathway-based, reaction-specific disease variant dataset and data model provide a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity.

systems biology↗

bioRxiv2019

Exosomes transmit retroelement RNAs to drive inflammation and immunosuppression in Ewing Sarcoma

Ewing sarcoma (EwS) is an aggressive childhood malignancy with a high propensity for metastasis. By analyzing cohorts of patients and age-matched healthy donors, we establish that EwS metastatic progression is accompanied by elevated plasma levels of multiple proinflammatory cytokines, interferons and extracellular vesicles (EVs). The latter were enriched with transcripts derived from LINE, SINE and ERV retroelements and from locus-specific pericentromeric regions, including HSAT2. We show that some of these RNAs, including HSAT2 and HERV-K, are selectively transmitted in EwS EVs and taken up by stromal fibroblasts and peripheral blood CD33+ myeloid cells and CD8+ T-cells, inducing immune exhaustion, immunosuppressive phenotypes and proinflammatory responses. Moreover, EwS EV-derived repeat RNAs were propagated and serially transmitted in recipient cell EVs, reminiscent of viral infection. As such, this study uncovers a novel mechanism driving cancer-associated inflammation, immunosuppression and metastatic progression.

cancer biology↗