InSyBio (Intelligent Systems Biology) is a biotechnology company delivering high quality products and services in precision medicine and nutrition.
United States
Based in United Kingdom
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🧬 Example focused tasks:
• Differential expression
• Proteomics QC
• Pathway enrichment
• Network analysis
• Biomarker modelling
• Data cleaning & imputation
Support can be scoped around the question you actually need answered.
#Omics #DataAnalysis
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📊 Need one focused bioinformatics analysis?
InSyBio Micro-Analysis Services cover RNA-seq, proteomics, biomarker discovery, ML-ready data preparation and more.
🌐 insybio.com/c-fixed-price-mi…
#Bioinformatics #InSyBio
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💡 Automation does not replace scientific judgment.
Good pipelines still depend on:
✅ Study design
✅ Data quality
✅ Validation
✅ Biological interpretation
The tool should support the question — not define it.
#Bioinformatics #MachineLearning
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🧬 Workflow integration is not only about speed.
It can also reduce unnecessary data transfers between tools and make the path from analysis → biomarkers → models easier to manage.
#ReproducibleResearch #BiomarkerDiscovery
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🚀 InSyBio Pipelines connects:
📊 Statistical analysis
🕸️ Network analytics
🎯 Biomarker discovery
🤖 Machine-learning models
A more continuous route from biomedical data to predictive insight.
🌐 insybio.com/insybio-pipeline…
#InSyBio #Bioinformatics
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🧬 A classification threshold of 0.5 is not a biological law.
The appropriate threshold depends on the cost of:
❌ False negatives
vs.
❌ False positives
Evaluate the model according to the actual research or clinical question.
#PredictiveAnalytics #PrecisionMedicine #InSyBio
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📊 For imbalanced biomedical datasets, look beyond accuracy:
✅ Sensitivity
✅ Specificity
✅ Precision
✅ F1
✅ Balanced accuracy
✅ MCC
✅ ROC-AUC / PR-AUC
And always inspect the confusion matrix.
#BiomarkerDiscovery #Biostatistics
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⚖️ 95% accuracy can still describe a useless biomedical classifier.
950 controls
50 disease cases
Predict everything as control → 95% accuracy.
Disease cases detected → 0.
Always check what sits behind the accuracy.
#Bioinformatics #MachineLearning
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🧬 InSyBio Interact can support PPI search, custom interaction datasets, network visualization, clustering and functional enrichment.
💻 Free one-month InSyBio Suite license:
insybio.com/get-a-free-one-m…
#InSyBioInteract #SystemsBiology
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🕸️ After identifying interesting proteins, ask the next question:
Do they interact?
Do they form modules?
Are particular functions enriched?
Network context can turn a list of molecules into testable biological hypotheses.
#NetworkBiology #Bioinformatics
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InSyBio retweeted
Beautiful study. There is so much in microbial genomes we still don’t understand. Exciting to see the use of genome language models powering the discovery of these cool new systems. Congrats to @_david_li, @garykbrixi, @brianhie, and the team!
Excited to share Minerva, our approach using genome language models for biological discovery! Using Minerva, we find that UG27 reverse transcriptase systems encode variable arrays of diverse ncRNAs with a shared structure, each templating a short DNA hairpin. With @garykbrixi.
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InSyBio retweeted
Can #AI move beyond prediction to explain disease?
This review outlines how trustworthy AI can link #MultiOmics, imaging and real-world data to mechanisms, robust validation and #PrecisionMedicine. @CQU1929
#OpenAccess #GenesAndDiseases: doi.org/10.1016/j.gendis.202…
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🔗 A protein list is not yet a biological network.
InSyBio Interact helps researchers explore predicted PPIs, protein information and interaction confidence in one connected workflow.
🌐 insybio.com/insybio-interact…
#Proteomics #Interactomics #InSyBio
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🤖 BioInfoLLM™ adds natural-language, evidence-grounded guidance inside InSyBio Suite.
Ask about methods.
Navigate workflows.
Interpret outputs.
Keep the biology in focus.
💻 Free one-month license:
insybio.com/get-a-free-one-m…
#BioInfoLLM #InSyBio #Bioinformatics
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🕸️ Networks are not the end of the workflow.
With InSyBio Suite, researchers can connect network analysis with statistical and ML-based biomarker discovery to move from relationships to predictive biosignatures.
#BioNets #BiomarkerDiscovery #MachineLearning
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🧬 One suite. Connected workflow.
DataStore
→ Interact
→ BioNets
→ Biomarkers
Move from data management to protein interactions, networks and predictive biosignatures.
🌐 insybio.com/
#InSyBioSuite #Bioinformatics #MultiOmics
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🔄 A strong cross-study result should survive more than one preprocessing choice.
Run sensitivity checks for:
✔️ Filtering
✔️ Normalization
✔️ Batch correction
✔️ Imputation
Robust biology > one “perfect” pipeline.
#Proteomics #Bioinformatics #InSyBio
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📊 Missing values are not all the same.
Before imputation, check whether missingness differs by:
• Study
• Platform
• Batch
• Experimental condition
Technical missingness can easily become a false biological signal.
#DataHarmonization #ReproducibleResearch
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🧬 Proteomics meta-analysis tip:
Do not merge first and troubleshoot later.
Start by harmonizing:
✅ Protein identifiers
✅ Sample metadata
✅ QC criteria
✅ Filtering rules
#Proteomics #Bioinformatics #MetaAnalysis
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