Science AI Journal
Biochemistry, Genetics and Molecular Biology · Research topic

Open research questions in Biomedical Text Mining and Ontologies

174 unresolved questions extracted from the limitations and future-work sections of 555 Biomedical Text Mining and Ontologies papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • The explain stage therefore surfaced a biomaterial-inspired mRNA-LNP depot bridge, but it still marked the pack as insufficient evidence for direct claims about vaccine adjuvant inclusion and long- term efficacy.

    Evidence-Grounded Frontier Mapping and Agentic Hypothesis Generation in Nanomedicine · 2026

  • The study focused on a specific task and dataset, - The results may not generalize to other languages or domains, - The study used a limited number of models and baselines

    Knowledge-enhanced LLMs for multilingual biomedical concept normalization: a multilingual benchmarking and behavioral analysis · 2026 · DOI

  • Investigating the use of other knowledge bases and enrichment methods, - Exploring the application of LLMs to other biomedical NLP tasks, - Analyzing the robustness of LLMs to different types of noise and errors

    Knowledge-enhanced LLMs for multilingual biomedical concept normalization: a multilingual benchmarking and behavioral analysis · 2026 · DOI

  • Further research is needed to understand the mechanisms of RBP dysfunction in neurodegenerative diseases. The study suggests that cross-disease signals should be interpreted cautiously and further research is needed to understand the relationships between different neurodegenerative diseases.

    Global research architecture of RNA-binding proteins in neurodegenerative diseases: a web of science bibliometric study with PubMed record verification, 2001–2025 · 2026 · DOI

  • The organization and evolution of the cross-disease research field of RNA-binding proteins in neurodegenerative diseases remain unclear. There is a need to characterize the global research architecture of RNA-binding proteins in neurodegenerative diseases.

    Global research architecture of RNA-binding proteins in neurodegenerative diseases: a web of science bibliometric study with PubMed record verification, 2001–2025 · 2026 · DOI

  • Recent advances in large language models (LLMs) provide a promising approach for simplifying complex medical information into patient-friendly language; however, their effectiveness in real-world patient education remains insufficiently explored through human evaluation.

    Medical Knowledge Simplification for Patients in the Era of LLMs: A Case Study on Diabetes · 2026

  • Gross brain findings help guide differential diagnosis, but their diagnostic value across major neurodegenerative diseases remains incompletely characterized.

    Diagnostic Value of Large Language Model-Extracted Gross Brain Findings in Neurodegenerative Diseases · 2026 · DOI

  • The complexity of integrating AI into medical practice. The need for regulatory frameworks to govern the use of AI in medicine. The challenge of distinguishing between AI's role as a supportive tool and as a therapeutic factor.

    Artificial Intelligence as an Object of Information Pharmacology: the Boundary Between a Supportive Tool and a Therapeutic Factor · 2026 · DOI

  • The current lack of distinction between AI as a supportive tool and as a therapeutic factor. The need for a conceptual framework to understand the role of AI in information pharmacology.

    Artificial Intelligence as an Object of Information Pharmacology: the Boundary Between a Supportive Tool and a Therapeutic Factor · 2026 · DOI

  • The rapid growth of relevant cell types, in vivo models, and biomaterial strategies makes it difficult to synthesize evidence across studies. Study designs are highly heterogeneous, making it difficult to compare findings across studies.

    KGBR: A Domain-Specific Knowledge Graph for Bone Regeneration Research · 2026 · DOI

  • KGBR development must incorporate methods to align mouse experimental evidence with human bone regeneration data, including standardized ontology mappings for orthologous genes, cell types, and signaling pathways across species to support translational research from preclinical to clinical applications.

    KGBR: A Domain-Specific Knowledge Graph for Bone Regeneration Research · 2026 · DOI

  • The complexity and heterogeneity of biobank-scale datasets pose substantial barriers to access and interpretation. The need for a reproducible, multi-metric evaluation framework to benchmark the capabilities of leading LLMs.

    La benchmarking large language models for extracting biobank-derived insights into health and disease · 2026 · DOI

  • The extent to which current general-purpose LLMs can retrieve and synthesize biobank-specific insights has not yet been systematically evaluated. There is a need for a reproducible, multi-metric evaluation framework to benchmark the capabilities of leading LLMs.

    La benchmarking large language models for extracting biobank-derived insights into health and disease · 2026 · DOI

  • Extracting longer phrases remains underexplored. Conventional named entity recognition has focused on short terms. Developing more general systems that can perform many tasks without manual creation and labeling of a training dataset is a challenge.

    Evaluating Encoder and Decoder Models for Extended Clinical Concept Recognition in Japanese Clinical Texts: Comparative Study With Weighted Soft Matching · 2026 · DOI

  • The study is limited to Japanese clinical texts and may not be generalizable to other languages or domains. The dataset used is relatively small, with approximately 20,000 case reports.

    Evaluating Encoder and Decoder Models for Extended Clinical Concept Recognition in Japanese Clinical Texts: Comparative Study With Weighted Soft Matching · 2026 · DOI

  • The selection bias introduced by excluding non-open-access publications and proprietary datasets. The limitation of literature-level text mining in capturing patterns of scientific discourse rather than direct biological measurements. The need to address methodological and translational limitations in interpreting the findings.

    Epigenomic Biomarker Discovery from Biomedical Literature: AI and Text Mining Toward Health Monitoring Frameworks · 2026 · DOI

  • The lack of systematic analysis of large-scale scientific literature in epigenomic biomarker research. The limited attention to the broader structure of epigenomic research at the literature level. The need for a scalable approach to synthesize accumulated knowledge and identify consistent patterns across studies.

    Epigenomic Biomarker Discovery from Biomedical Literature: AI and Text Mining Toward Health Monitoring Frameworks · 2026 · DOI

  • There is a lack of specialized intelligent QA systems tailored for the SEP domain. Existing general-purpose large language models show limitations in knowledge retrieval accuracy, semantic matching, and legal compliance of generated content.

    SEP-LLM: Professional QA in the SEP Domain Using Retrieval-Augmented LLMs · 2026 · DOI

  • Future work may explore finer-grained knowledge injection mechanisms, more powerful multi-hop reasoning architectures, and stricter domain-adaptive training strategies to continually improve the system's performance in complex professional domains. Future work will explore multi-modal knowledge injection, dynamic knowledge base updates, and interpretable reasoning mechanisms to further enhance the system’s applicability, reliability, and explainability in real-world industrial scenarios, providing a feasible technical solution for intelligent question answering in the SEP domain and broader specialized vertical fields.

    SEP-LLM: Professional QA in the SEP Domain Using Retrieval-Augmented LLMs · 2026 · DOI

  • The study identifies a gap in the comparison of BioBERT and CNN models for neurological disorder detection. The gap is due to the lack of systematic evaluation of these models in clinical text understanding.

    Performance Evaluation of BioBERT and CNN Models for Neurological Disorder Detection · 2026 · DOI

  • Abubakar Sadiq Muhammad, 2026, 14:3 ISSN (Online): 2348-4098 ISSN (Print): 2395-4752 International Journal of Science, Engineering and Technology An Open Access Journal Therefore, Furthermore, the study concludes that traditional neuroscience models, while foundational, are often limited by their inability to scale, adapt to heterogeneous data, or process unstructured text.

    Performance Evaluation of BioBERT and CNN Models for Neurological Disorder Detection · 2026 · DOI

  • Existing approaches treat entity alignment as a static matching problem, ignoring query context and cross-system asymmetry - The need for a framework that can capture asymmetric and many-to-many correspondence across heterogeneous knowledge systems

    Query-Conditioned Knowledge Alignment for Reliable Cross-System Medical Reasoning · 2026

  • Specialized cell-type models trained exclusively on single-cell data or domain-specific subsets. Incorporation of additional omics modalities to construct richer joint embedding spaces for unpaired data. Applying the model as a classifier or guiding signal for generative diffusion models of transcriptomes.

    mmContext: an open framework for multimodal contrastive learning of omics and text data · 2026 · DOI

  • There is no accessible, standardized framework for systematic comparison of omics representations with different text encoders. Existing implementations of multimodal omics/text models remain difficult to customize and are not integrated into widely supported ecosystems.

    mmContext: an open framework for multimodal contrastive learning of omics and text data · 2026 · DOI

  • Genes/proteins and the three Gene Ontology categories aligned cleanly across PrimeKG and Hetionet (mutual coverage 94-99%), but disease overlap was sparse: only 0.

    Beyond Identifier Matching: An Empirical Characterization of Failure Modes in Biomedical Knowledge Graph Integration · 2026 · DOI

Most-cited papers in Biomedical Text Mining and Ontologies

Most recent work

Find a gap in your own Biomedical Text Mining and Ontologies sub-topic

This page shows what the Biomedical Text Mining and Ontologies literature already flags as unresolved. To narrow it to your specific question, run the guided finder — it searches the gap library on demand and checks candidates against 250M+ OpenAlex works.

Open the Research Gap Finder →

Related topics in Biochemistry, Genetics and Molecular Biology

Gut microbiota and health
1,024 open questions
Single-cell and spatial transcriptomics
602 open questions
Genetic Associations and Epidemiology
393 open questions
Antibiotic Resistance in Bacteria
360 open questions
Inflammatory Bowel Disease
353 open questions
Extracellular vesicles in disease
305 open questions
Mitochondrial Function and Pathology
296 open questions
Human-Animal Interaction Studies
294 open questions
174 open questions have been extracted from the limitations and future-work passages of 555 Biomedical Text Mining and Ontologies papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

Tools for your next paper

Gaps & Literature SearchFind open questions in any field — 120,000+ open gaps mined from our own library.Pre-CheckIs your paper ready? A Tier 1–5 acceptance probability in seconds.Journal FinderA ranked shortlist of target journals from a 17,500-venue index.Duplicate Publication CheckerCheck prior-publication & salami-slicing risk across 8 sources.Citation GeneratorFreeA DOI or title → APA, MLA, Vancouver, Chicago, BibTeX, RIS. No signup.Graphical Abstract MakerFreeTurn your findings into a colorblind-safe graphical abstract.

Compare the category — Honest roundups of the AI research tools, ours listed alongside the alternatives.

Command palette

Jump anywhere, run any action.