BGPT: gpt 2

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Quick Explanation Copied

I don’t see a specific question/command in your message. Paste your scientific question (or a file + goal), and I’ll respond with fully inline-cited, graph-first results using your BGPT “raw-data search” papers.

Long Explanation

What I need from you

Please provide one of the following:

1) Your exact question

Example formats: “Analyze X vs Y”, “Summarize best evidence for Z”, “Design an experiment to test H”, “Create graphs comparing AUC/calibration across studies”.

2) A bioinformatics command

Example: “Run an end-to-end pipeline to analyze my FASTA/VCF and produce QC + plots.” (Upload files, then tell me outputs.)

3) Choose a BGPT science action

If you upload files and tell me the target outputs, the agent will iteratively analyze them.

Feedback:

Updated: April 25, 2026

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1. A GPT-based multi-disease progression model (Delphi-2M) trained on UK Biobank data predicts incidence rates for over 1,000 diseases, generates future health trajectories, and generalizes to Danish population data, with explainability analyses revealing temporal co-morbidity patterns and data-bias limitations. [2025]

9QualityResults Limitations Context Blindspots Methods Sample Conflict

↗ Paper Review ↗ Full Paper

2. The study introduces mRNA-GPT, a GPT-2–based generative mRNA language model trained on domain-specific mRNA coding sequences across bacteria, archaea, and eukaryotes, which can be fine-tuned to optimize translation efficiency, stability, or expression, enabling efficient design of coding sequences for mRNA therapeutics and vaccines. [2025]

8QualityResults Limitations Context Blindspots Methods Sample Conflict Data

↗ Paper Review ↗ Full Paper

3. An adapter-based approach, PsychAdapter, conditions continuous psychological trait scores into every transformer layer to generate trait-reflective text across personality, mental health, and demographic domains, with high alignment to target traits demonstrated by human raters and automated evaluators and generalization across text domains and models. [2026]

9QualityResults Limitations Methods Sample Conflict Data

↗ Paper Review ↗ Full Paper

4. This work introduces an analog in-memory computing architecture using gain-cell arrays to perform attention computations for large language models, enabling ultra-fast, energy-efficient inference with a hardware-aware mapping of pre-trained GPT-2 weights and demonstrating GPT-2–level accuracy on NLP benchmarks despite non-ideal circuit behavior. [2025]

9QualityResults Limitations Context Blindspots Methods Sample Conflict Data

↗ Paper Review ↗ Full Paper

5. Few-shot fine-tuned large language models leveraging literature-derived prior knowledge can predict drug-pair synergy in seven rare cancer tissues with limited data, achieving competitive accuracy and often outperforming data-driven baselines when external data are scarce or out-of-distribution. [2024]

7QualityResults Limitations Context Blindspots Methods Sample Conflict Data

↗ Paper Review ↗ Full Paper

Key Insight

Without a concrete scientific query, any “answer” would be a guess; the most truthful next step is to lock the target outcome and evidence type before generating graphs.

Keep Exploring

What exact biological hypothesis or task do you want to evaluate (and what evidence format—graphs, effect sizes, protocols)?

What data do you have (FASTA/VCF/expression counts/clinical outcomes), and what outputs do you want (QC plots, embeddings, evaluation metrics)?

Science Movie

Make a narrated HD Science movie for this answer ($32 per minute)

Discussion

BGPT Bias

I default to requiring a precise target because scientific accuracy depends on an explicit objective and evidence scope.

Stay current without chasing every paper.

Know what changed, what holds up, and what remains uncertain. Every Friday. No ads.

Traceable Claims in Bioinformatics

See what computational analyses actually reported, with provenance for every claim.Know what the science actually supports before you trust the answer.

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Quick Explanation Copied

Long Explanation

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6. Unified a pre-trained language model framework to jointly perform spatial-temporal forecasting and imputation on traffic data, enabling zero-shot and few-shot learning through spatial-temporal tokenizers and a sandglass attention mechanism. [2025]

7. KG-RAG retrieval augmented generation integrating knowledge graphs with vision–language radiology models yields more accurate and informative natural language explanations for thoracic pathologies in chest X-ray images on the MIMIC-NLE dataset. [2025]

Ask a Follow-Up

Key Insight

Without a concrete scientific query, any “answer” would be a guess; the most truthful next step is to lock the target outcome and evidence type before generating graphs.

Keep Exploring

What exact biological hypothesis or task do you want to evaluate (and what evidence format—graphs, effect sizes, protocols)?

What data do you have (FASTA/VCF/expression counts/clinical outcomes), and what outputs do you want (QC plots, embeddings, evaluation metrics)?

Science Movie

Make a narrated HD Science movie for this answer ($32 per minute)

Discussion

BGPT Bias

I default to requiring a precise target because scientific accuracy depends on an explicit objective and evidence scope.

Stay current without chasing every paper.

My BGPT

Trending

Traceable Claims in Bioinformatics

See what computational analyses actually reported, with provenance for every claim.Know what the science actually supports before you trust the answer.

Explore by Goal

Quick Explanation Copied

Long Explanation

Top Data Sources ExportMCP

6. Unified a pre-trained language model framework to jointly perform spatial-temporal forecasting and imputation on traffic data, enabling zero-shot and few-shot learning through spatial-temporal tokenizers and a sandglass attention mechanism. [2025]

7. KG-RAG retrieval augmented generation integrating knowledge graphs with vision–language radiology models yields more accurate and informative natural language explanations for thoracic pathologies in chest X-ray images on the MIMIC-NLE dataset. [2025]

Ask a Follow-Up

Key Insight

Without a concrete scientific query, any “answer” would be a guess; the most truthful next step is to lock the target outcome and evidence type before generating graphs.

Keep Exploring

What exact biological hypothesis or task do you want to evaluate (and what evidence format—graphs, effect sizes, protocols)?

What data do you have (FASTA/VCF/expression counts/clinical outcomes), and what outputs do you want (QC plots, embeddings, evaluation metrics)?

Science Movie

Make a narrated HD Science movie for this answer ($32 per minute)

Discussion

BGPT Bias

I default to requiring a precise target because scientific accuracy depends on an explicit objective and evidence scope.

Stay current without chasing every paper.

My BGPT

Trending

Top Data Sources Export MCP