Open research questions in Genetics, Bioinformatics, and Biomedical Research
220 gap statements mined from Genetics, Bioinformatics, and Biomedical Research papers in our 7.9M-paper local library, which holds 1,444 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.
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What the literature leaves open
The duration of the training was identified as the largest limiting factor. The computationally intensive bioinformatics sessions were challenging for some fellows. The lack of access to local bioinformatics expertise and training, lack of computational infrastructure, and internet access instability are major challenges in low- and middle-income countries in Africa.
Building Pathogen Genomic Sequencing Capacity in Africa: Centre for Epidemic Response and Innovation Fellowship · 2025 · DOIWe argue that literacy alone is insufficient in a field where data leakage, incomplete metadata, ecological confounding, inappropriate model selection and unverified generative-AI outputs can produce convincing but biologically misleading conclusions.
The lack of understanding of the general principles and specific mechanisms governing the dynamics of genetic information in living systems. The need to establish the link between genetic information and thermodynamic equilibrium.
Limited understanding of biologically significant associations among amino acids.
Unraveling protein secrets: machine learning unveils novel biologically significant associations among amino acids · 2026 · DOINew mathematical tools are needed to address the challenges of big data in bioinformatics. There is a growing interest in scalable optimization methods that can manage petabyte-sized genomic arrays. The development of mathematical tools that can integrate highly heterogeneous data records is needed.
The need for a better understanding of the underlying biological processes involved in appetite stimulation and obesity. The lack of effective treatments for chronic kidney disease. The need for further research on the role of autophagy and melanophagy in skin aging.
Further studies are needed to assess the effectiveness of the CURE model in improving student engagement, retention, and scientific identity. Further studies are needed to explore the use of other wild yeast strains and fermentation products. Further studies are needed to develop and refine the CURE model for use in other institutions and contexts.
Declaration of Fermentation: Community-Embedded Wild Yeast Bioprospecting as a Model for Place-Based CURE Design · 2026 · DOIThere is a need for novel CURE models that engage students in genuine inquiry and promote community partnerships. There is a need for proof of concept studies demonstrating the feasibility and logistical achievability of these models.
Declaration of Fermentation: Community-Embedded Wild Yeast Bioprospecting as a Model for Place-Based CURE Design · 2026 · DOIThe limited size of the sustained-activity dataset. The need for a data-driven approach to select high-potency DNAzymes.
CleaveSmart: deciphering the puzzle of rational 10–23 DNAzyme selection through interpretable AI insights · 2026 · DOIVariant interpretation (VI) is crucial to genomic testing, yet there are no agreed professional competencies in VI, career pathways are ill-defined for some professions, and there is limited literature on educational needs and programs.
Variant interpretation training for the genomics era: Learning outcomes to inform professional competencies and education · 2026 · DOIThe AIs performed poorly when required to analyze image- and DNA sequence-based questions. The AIs performed poorly at higher levels of cognitive complexity as defined by Bloom's Taxonomy. There is a need to adapt assessments based on AI ability, particularly through the utilization of image- and sequence-based questions.
Artificial Intelligence Performance in Introductory Biology: Passing Grades but Poor Performance at High Cognitive Complexity · 2025 · DOIThe need to overcome the limitations of the modeling tool and the difficulties students face when building models.
The lack of interpretability of deep learning models is a challenge in understanding how predictions reflect biological mechanisms. The need for large amounts of high-quality data is a limitation in applying deep learning to computational biology. The inability of deep learning models to multitask is a challenge in analyzing complex biological data.
However, no matter the type of AI and ML method or technique utilized, there are issues of importance that are not well understood or considered during their application.
They can include among other issues, the selection of samples and sampling protocols, the lack of understanding of the physical effects of sample presentation on the collected signal, the utilization of few samples during model development, the issues associated with model overfitting as well as the lack of validation of the models.
Establishing appropriate bioinformatics infrastructures and computational resources is challenging.
Computational Resources and Infrastructures for a Novel Bioinformatics Laboratory: A Case Study · 2025 · DOIThere is still no comprehensive theory concerning the use of narrative in science classrooms. Too little data is available on the use of narrative in science classrooms. The majority of existing studies have focused on interventions centered around the consumption of narrative material by the students.
The Potential of Narrative for Understanding Protein Biosynthesis in the Context of Viral Infections · 2024 · DOIThe paper demonstrates that Cysteine clusters with polar amino acids rather than Methionine despite both containing sulfur atoms, suggesting overall physicochemical properties dominate specific chemical features, but does not systematically test this principle across amino acid pairs with shared chemical elements to establish the relative weighting of feature classes.
Unraveling protein secrets: machine learning unveils novel biologically significant associations among amino acids · 2026 · DOIThe predictive performance of all models is lower for rapid-activity datasets. The study uses a limited size of the sustained-activity dataset (n = 38). The pipeline is designed for sustained catalytic activity and may not be applicable to rapid-activity datasets.
CleaveSmart: deciphering the puzzle of rational 10–23 DNAzyme selection through interpretable AI insights · 2026 · DOIAI applications in life sciences are reviewed across drug discovery, genomics, and marine biology, but none of these studies empirically compares AI model performance, interpretability, or real-world implementation outcomes across these distinct domains to identify domain-specific failure modes or transferability barriers.
Further analysis of the role of genetic information in maintaining non-equilibrium conditions. The study of the application of enzyme-accelerated reactions in biotechnology.
The study only involved 'second-year students obtaining a degree in Primary Education', - The study had a limited sample size of 'n= 86' in the experimental group and 'n = 68' in the control group, - The study did not compare the results to other inquiry-based modeling…
Create hybrid models by incorporating other machine learning techniques to improve performance and interpretability, - Develop techniques to clarify deep learning's decision-making…
Reliance on exclusively self-report data, - Possibility of participants' shifting interpretation of the questions over time, - Participants' potentially imperfect insight into their own abilities, - Lack of objective measures…
Modular, focused data science education improves biomedical learners’ abilities: A study of the Data and Analytics for Research Training (DART) program · 2025 · DOIIncorporating objective measures of learning in the design, - Assessing the effectiveness of the DART program with a more diverse population, - Investigating the long-term effects of the DART program on learners'…
Modular, focused data science education improves biomedical learners’ abilities: A study of the Data and Analytics for Research Training (DART) program · 2025 · DOI
Most-cited papers in Genetics, Bioinformatics, and Biomedical Research
- Database resources of the national center for biotechnology information · Nucleic Acids Research · 2021 · 2,910 citations
- From molecular to modular cell biology · Nature · 1999 · 2,902 citations
- Intracellular Aspects of the Process of Protein Synthesis · Science · 1975 · 2,584 citations
- Central Dogma of Molecular Biology · Nature · 1970 · 2,366 citations
- KEGG mapping tools for uncovering hidden features in biological data · Protein Science · 2021 · 730 citations
- Database resources of the National Center for Biotechnology Information in 2025 · Nucleic Acids Research · 2024 · 472 citations
- Biosemantics · The Journal of Philosophy · 1989 · 421 citations
- Using the PyMOL application to reinforce visual understanding of protein structure · Biochemistry and Molecular Biology Education · 2016 · 413 citations
- Biological Corridors: Form, Function, and Efficacy · BioScience · 1997 · 337 citations
- Empowering biomedical discovery with AI agents · Cell · 2024 · 312 citations
Most recent work
- Resisting AI slop · Science · 2026
- Structural motif search across the protein universe with Folddisco · Nature Biotechnology · 2026
- Unraveling protein secrets: machine learning unveils novel biologically significant associations among amino acids · Network Modeling Analysis in Health Informatics and Bioinformatics · 2026
- Open and sustainable AI: challenges, opportunities and the road ahead in the life sciences · Nature Methods · 2026
- The major histocompatibility complex: a key to a better understanding of evolution · PubMed · 2026
- PLANeT: Understanding and leveraging the genome of land plants for a sustainable future · Cell · 2026
- Rethinking bioinformatics expertise in the era of artificial intelligence · npj Digital Medicine · 2026
- Variant interpretation training for the genomics era: Learning outcomes to inform professional competencies and education · The American Journal of Human Genetics · 2026
- Declaration of Fermentation: Community-Embedded Wild Yeast Bioprospecting as a Model for Place-Based CURE Design · bioRxiv · 2026
- Advancing molecular and cellular neuroscience: Vision and priorities from the new editor-in-chief · Molecular and Cellular Neuroscience · 2026
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