Work backward from target compounds and candidates
Connect disease context, existing data, imaging, omics, and structural indicators to define the efficacy, toxicity, and mechanism conditions to explore.
Integrate Analysis System IAS
Connect imaging, NGS, flow cytometry, mass spectrometry, and molecular structure data by experiment.
IAS is not a replacement for every point tool. It is a web-based workflow layer that brings fragmented research data, analysis procedures, review records, and report creation into the same context.
- Absorb format differences
- Standardize analysis steps
- Support collaborative review
Experiment-level integrationConnect imaging, NGS, flow, mass-spec, and molecular structure into one research decision.
IAS is a workflow layer between point tools and LIMS
IAS does not replace modality-specific tools. It connects experiment-level data, analysis, review, and reporting into one decision surface.
- Connect
Bundle assay outputs
Organize imaging, flow, genomics, mass spectrometry, and molecular structure outputs by experiment.
- Analyze
Work in one environment
Handle modality-specific analysis methods in the same workspace and reduce manual handoffs.
- Link
Connect cross-assay evidence
Tie multiple assay results into one research decision so comparison and interpretation move faster.
- Govern
Create reviewable output
Carry analysis history, checks, and report creation toward reproducible final outputs.
Feed discovery goals back into simulation and wet-lab planning
IAS organizes target compounds, candidate drugs, hypotheses, evaluation metrics, and next conditions so analysis results can shape simulation and experimental planning before the next run.
Beyond improving analysis accuracy, interpretation, and reporting efficiency, IAS raises experiment-design quality and shortens the research cycle from candidate discovery to wet validation.
Reflect findings in simulation and experiment design
Feed promising conditions, comparison groups, and measurement parameters into the next in silico review or wet-lab plan so trial order becomes clearer.
Reduce wet-lab research effort
Screen out lower-promise conditions earlier and focus experiments, checks, and reviews where they matter, reducing effort in both analysis work and wet-lab research.
NEW FEATURE
Now supports ChatGPT and LifeAnalytics' proprietary generative AI app
Helping researchers summarize, interpret, and draft reports from complex analysis results through natural language instructions.
LifeAnalytics IAS now supports ChatGPT and LifeAnalytics' proprietary generative AI application. Using research data, analysis history, experiment records, analysis summaries, and report context, IAS helps researchers summarize, interpret, create reports, and draft scientific manuscripts from complex life science analysis results.
IAS supports multiple analysis areas including image analysis, gene analysis, flow cytometry, mass spectrometry, molecular structure analysis, spatial multi-layer multi-omics analysis, and integrated analysis.
- Summarize and interpret results using natural language
- Organize multiple types of life science analysis data
- Support report creation and manuscript draft preparation
Implementation of five representative methodologies used in research and development and integrated analysis
IAS centrally manages representative research data such as image analysis, flow cytometry, next generation sequencing, molecular structure, and mass spectrometry in the cloud.
IAS analysis capabilities
Genome Analysis
Visualization, alignment, assembly, and annotation of DNA and protein sequences.
Mass Spectrometry
Acquisition, processing, and analysis of mass spectrometry data, including metabolomics.
Molecular Structure Analysis
High-accuracy prediction of 3D protein structure from amino acid sequences.
Integrated Analysis
AI-assisted discussion reports based on individual analysis results.
Imaging
Image analysis for cells and tissue sections, including 3D, Timelapse, HCS, and pathology.
Flow Cytometry
Flow cytometry analysis such as SPADE, U-MAP, and dot plots.
IAS specification details
IAS Specifications: Analysis Modes, AI Models, and Support Functions
Handle imaging, flow cytometry, genomics, mass spectrometry, molecular structure, and integrated analysis in one research workbench.
IAS is not a single image-analysis application or a collection of isolated point tools. It brings imaging, flow cytometry, genomics, mass spectrometry, molecular structure analysis, integrated analysis, and data management into one research workbench experience.
IAS AI output does not guarantee clinical diagnosis. Interpretation of pathology images, medical images, genomics, molecular structure, and mass-spec results should be combined with specialist review, raw-data inspection, standard methods, and external validation.
Workflow diagramAnalysis mode cards
Each card summarizes inputs, outputs, and review points at a practical evaluation level.
Imaging / DL-ML
- Target data
- Microscopy, pathology, cell, materials, animal time-series, and spatial omics images
- Representative input
- Microscopy, WSI, CT/MRI-like images, timelapse, 3D volume, spatial omics images
- Main output
- Segmentation, ROI analysis, tracking, quantification tables, pathology-support reports
- Review points
- Image quality, ROI settings, mask accuracy, positivity criteria, specialist review
FlowCyto
- Target data
- Flow cytometry and spectral cytometry
- Representative input
- FCS, panel metadata, compensation matrix, gate definitions
- Main output
- Compensation, QC, manual gates, clustering, UMAP/t-SNE, statistics
- Review points
- Compensation, channel names, QC exclusion rules, gate hierarchy, threshold history
Genomics
- Target data
- Sequence analysis, NGS, single-cell, CRISPR, multi-omics
- Representative input
- FASTA, FASTQ, BAM, VCF, H5AD, tabular data
- Main output
- QC, alignment, variants, single-cell clusters, annotations, reports
- Review points
- Genome build, QC, depth, population frequency, reference data, batch correction
MassSpec
- Target data
- MS, MSI, proteomics, metabolomics, lipidomics, DIA, targeted quant
- Representative input
- raw, mzML, mgf, ms2, wiff, peak tables, identification tables, quant tables
- Main output
- Peak detection, identification, quantification, database matching, MSI spatial analysis
- Review points
- QC, blank, batch correction, FDR, standards, retention time, MS/MS evidence
Molecular Structure
- Target data
- Structure prediction, docking, molecular dynamics, function inference
- Representative input
- Sequences, PDB, mmCIF, ligands, complexes, conditions
- Main output
- Predicted and public structures, docking candidates, MD analysis, validation reports
- Review points
- Confidence, pLDDT/PAE, protonation, box, charge, force field, experimental structures
Integrate
- Target data
- Cross-mode integration and decision support
- Representative input
- Mode result tables, HDF5, JSON, CSV, sample IDs
- Main output
- ID mapping, statistical integration, cross-modal relations, Gen Report
- Review points
- Sample ID mapping, missingness, units, batches, correlation versus causation
DB Manage / Sample DB
- Target data
- Data management, metadata, experiment history
- Representative input
- Uploaded files, experiment names, sample tags, analysis history
- Main output
- Input history, file references, mode estimation, re-analysis paths
- Review points
- Sample ID consistency, history, auditability, re-analysis readiness
Analysis-mode details and review points
Long model inventories are grouped by purpose so readers can see how each model is used and what should be checked before interpreting outputs.
Imaging and DL/ML model useMore details
IAS imaging modes cover Tissue, Cell, Material, Semicon, Animal, and ML workflows so teams can choose models by purpose.
Tissue
TissueNet, Foxp3 Spatial, Foxp3 DAB Spatial, Ki67-Br, Pathology, CT/MRI Segment, Spatial Omics, TissueNT2, Thyroid, and Lymph support tissue segmentation, ROI quantification, positivity review, spatial distribution, and multi-channel statistics.
Cell
Cyto, Cyto2, SAM, 2Dtracker, 3Dtimelapse, Nuclei, Nucleus01, Confluency, CM-CellCycle, LiveCell, CP, CPx, TN1-3, LC1-4, Single Cell Protein, 3DVD, LFcell02, and CellPaintingV3 support cell segmentation, tracking, morphology profiling, localization, and state review.
Material / Semicon / Animal / ML
Pore Analysis, Layer, Microridge, Mfiber1, Mfiber2, Wafer, Mouse Dynamics Tracking, and Pixel Classification support pore, layer, ridge, fiber, wafer, animal motion, and user-defined pixel-classification reviews.
Pathology mode: ROI editing, visual similarity, and finding-candidate supportMore details
Pathology mode combines local pathology processing, ROI editing, vision-language assistance, visual similarity, and nuclei/cell segmentation support.
WSI / ROI
OpenSlide, tifffile, OpenCV, and LAB/HSV/RGB Magic Wand support tissue masks, tile heatmaps, overlays, and color-space ROI editing.
AI support
Qwen2.5-VL + LoRA assist, ResNet152 visual similarity, and DeepLIIF biomarker support help generate descriptions, hypotheses, similar-image candidates, and biomarker-support summaries.
Segmentation
checkpoint-gated tumor segmentation, StarDist H&E nuclei, Cellpose-SAM service, and InstanSeg service provide candidate segmentation for tumor regions, nuclei, and cells.
This is not a diagnostic function. Outputs are research and review support for specialist-led pathology review.
FlowCyto: compensation, QC, gates, clustering, and statistics in one flowMore details
IAS connects FCS input, compensation, QC, gates, embedding, clustering, statistics, and reporting.
Compensation / QC
Compensation, spectral unmixing, PeacoQC, DataQC, doublet checks, and margin checks help review spillover, spectral overlap, abnormal events, flow-rate drift, doublets, and margin events.
Gate / Embedding
Gate editor, Boolean gates, UMAP, t-SNE, opt-SNE, and viSNE help preserve manual thresholds and inspect high-dimensional cytometry data.
Cluster / Statistics
FlowSOM, SPADE, CITRUS, population statistics, and marker summaries support population comparison, MFI review, figures, and reports.
Embeddings are visualizations; interpretation should be checked against marker expression and manual gates.
Genomics: sequences, NGS, single-cell, CRISPR, and Multi-OmicsMore details
IAS organizes sequence similarity, alignment, variants, single-cell analysis, reference mapping, and multi-omics evidence by experiment.
Sequence / Variant
BLAST, MSA, Phylogeny, CRISPR, QC & Alignment, Variant Calling, Joint Genotyping, and Annotation connect sequence review to variant and annotation review.
Browser / Single-cell
Genome Browser and Single-cell Async support genomic-region inspection, variants, gene models, normalization, HVG, PCA, clustering, UMAP, and marker detection.
Advanced / Multi-Omics
Harmony, scGPT, cell annotation capability checks, and Multi-Omics connect batch correction, reference mapping, cell-type annotation candidates, expression, variants, phenotypes, and other modes.
Check genome build, QC, depth, population frequency, labeled references, batch effects, missingness, and unit alignment.
MassSpec: peak detection, identification, quantification, MSI, and spectral similarityMore details
IAS connects raw/mzML/mgf/wiff inputs to peak features, identification, quantification, QC, database matching, reports, and multi-omics.
Metabolomics / Lipidomics
MS-DIAL, XCMS, MZmine, MS-FINDER, MS-CleanR, LipidSearch, and LipidBlast outputs are organized for candidate review and quantification.
Proteomics / MSI
MaxQuant, Proteome Discoverer, FragPipe, Mascot, Byonic, Spectronaut, DIA-NN, OpenSWATH, Prosit, SCiLS Lab, Cardinal, MSiReader, METASPACE, and OpenMSI outputs can be reviewed as part of the same workflow.
Target / AI / Multi-omics
MRM/SRM/PRM, MRMProbs, DeepNovo, Spec2Vec, MS2DeepScore, AlphaPept, mixOmics, MOFA(+), DIABLO, and OmicsNet outputs can be tied back to research decisions.
AI candidates should be verified with database matching, standards, MS/MS evidence, FDR, QC, blanks, and batch correction.
Molecular Structure: structure prediction, docking, MD, and validation reportsMore details
IAS helps review the path from Sequence/PDB/Ligand to structure prediction, docking, MD, validation, and reports.
Structure prediction
Monomer and complex structure prediction, public structure retrieval, and pLDDT/PAE review are handled as review inputs.
Docking / MD
GNINA, AutoDock-family, LightDock path, OpenMM, and mdtraj support binding-pose candidates, scores, binding-site review, RMSD/RMSF, interactions, and solvent-condition review.
Validation / Extensions
Validation quality checks, reports, function annotation, spectrum prediction, knowledge graph, QM, and FEP scaffolds help organize quality and extension candidates.
Check confidence, pLDDT/PAE, protonation, box, charge, ligand preparation, force field, solvent, temperature, and simulation length.
Integrate / DB Manage: sample IDs, experiment history, and evidence maturityMore details
IAS connects imaging, genomics, mass spec, flow cytometry, molecular structure, and reports around a consistent sample ID.
Mapping
sample ID and provenance mapping connect sample IDs, experiments, files, and preprocessing history across modes.
Statistics / Cross-modal
compute-statistics, random-effects meta-analysis, and cross-modal review connect effect sizes, confidence intervals, heterogeneity, imaging features, gene expression, metabolites, and population ratios.
Report / DB
Gen Report, report history, evidence maturity, DB Manage, and Sample DB help preserve report context, input history, file references, mode estimation, and re-analysis paths.
For clinical research support, keeping the same sample ID across Imaging, Genomics, MassSpec, and FlowCyto is critical.
Support functions: Support Chat, Patho Chat, and Q&A HelpMore details
Support functions reduce uncertainty during analysis by connecting operation guidance, knowledge search, ROI questions, and help dialogs.
Support Chat
Support Chat connects operation guidance, inquiry handoff, knowledge search, and AI-answer support for Imaging, Genomics, FlowCyto, Molecular, MassSpec, and Integrate.
Patho Chat / ROI Pathology Chat
Patho Chat combines ROI crops, feature extraction, similarity candidates, and Qwen-family LLM support to provide finding candidates, differential candidates, and suggested checks under pathology-specialist review.
Q&A / Help
Q&A icons and Help screens reduce operation mistakes through tooltips, Quick Start, Help dialogs, shortcut explanations, and Support Chat / Patho Chat visibility controls.
Patho Chat does not replace pathology review. Outputs are confirmation support and hypothesis-generation support for selected ROIs.
Five points to check during IAS evaluation
- Input typeWhether images, FCS, FASTQ/BAM/VCF/H5AD, mzML/raw, PDB/mmCIF, or integrated tables fit the target mode.
- Model or engine purposeWhat segmentation, tracking, annotation, clustering, docking, MD, or spectral matching output actually means.
- Output unitWhether the output is ROI, cell, nucleus, population, variant, peptide/protein, metabolite/lipid, structure, or cross-sample statistics.
- Validation itemsWhether QC, thresholds, confidence, FDR, reference databases, external standards, and specialist review remain visible.
- Support functionsWhether Support Chat, Patho Chat, and Q&A / Help give the right workflow guidance in context.
Check IAS fit with your own data
Your target data, analysis problem, and evaluation timing do not need to be fully organized. We can review the appropriate analysis modes and implementation path with you.
Demo consultationComprehensive coverage of analytical methods in fundamental research
Analytical methods for fundamental research are unified so researchers can work in the same environment with reproducible workflows.
Additional development of proprietary AI and features
We support additional proprietary AI and analysis features tailored to your goals, helping automate the entire research process.
Features of the IAS Platform
Coordinate and manage the entire lab
Manage data, analysis, and reports in one web system.
Complete Web System
Use the same analysis platform in collaborative and remote environments without local installation.
24-hour support via chat function
Smoothly proceed with questions and checks during analysis work.
Robust Data Management
Designed for compatibility with data management, leak prevention, and regulatory needs.
Generative AI Suggestions for Unique Selling Points
Support discovery of notable points from images and analysis results.
Organized support for many research formats
Supports integration of many data formats used in research settings.
User Feedback
Standardized analysis work
Specialized analysis procedures can be shared more easily, improving reproducibility in remote collaboration.
Efficiency across the lab
Central management of multiple data formats reduces the time required for analysis and reporting.
Explore 400+ supported formats by category
Instead of a long extension list, representative formats are grouped by research workflow and data type. For formats not shown here, share example files, instrument names, and desired outputs.
Representative data formats by category
Microscopy and bioimagingRepresentative research image formats from OME-TIFF, confocal, slide scanners, and electron microscopy.
- .ome.tiff
- .ome.tif
- .ome.xml
- .czi
- .lsm
- .lif
- .nd2
- .oib
- .oif
- .oir
- .vsi
- .svs
- .ndpi
- .qptiff
- .dm3
- .dm4
- .mrc
- .mrcs
General image, video, and documentsCommon image, video, tabular, HTML, and XML files used before and after analysis.
- .tif
- .tiff
- .png
- .jpg
- .bmp
- .gif
- .avi
- .mov
- .csv
- .txt
- .xml
- .html
- .h5
- .hdf
NGS and genomicsSequence, alignment, variant, and array-related data organized by experiment.
- fastq
- fasta
- bam
- vcf
- cel
- chp
- arr
- idat
Flow cytometry and qPCRCell population analysis, digital PCR, and instrument outputs with experiment metadata.
- stilla
- rdml
- .pnl
- .rdpnl
- .exp
- .xml
- .csv
Mass spectrometry and chromatographyRaw data, converted data, and vendor formats used around mass spectrometry analysis.
- mzml
- raw
- wiff
- d
- .spc
- .std
- .dat
- .res
Molecular structure, materials, and QCMolecular structure, materials observation, semiconductor, and quality-control inspection outputs.
- .cif
- sdf
- qip
- eds
- lmd
- .sxm
- .afm
- .stp
- .map
- .rec
Please contact us for formats not listed above.
Good Compatibility with Data Management, Leak Prevention and Regulation
Support data management that considers regulatory requirements such as 21 CFR Part 11.
Rich visualization tools
Visualization tools help researchers inspect analysis results intuitively.
Drafting reports and papers
Support report and manuscript draft creation from analysis results.
Achieving Complete Laboratory Automation
Connect analysis, management, and reporting to improve the entire lab workflow.
Application Examples by Analysis Mode
Each card separates the input data, the outputs IAS organizes, and the research decision it supports. Flow Cytometry, NGS, Molecular Structure, and MassSpec are treated as first-class analysis modes alongside Imaging.
Imaging: Drug efficacy and toxicity inference
Image analysis and Cell Painting
Extract morphology, organelle, and cluster features from cell images and connect them with disease context and known compound tendencies.
- Inputs
- HCS images, Cell Painting images, tissue or cell images, treatment conditions
- Outputs
- Morphology features, clusters, regions of interest, compound and disease similarity
- Decision use
- Prioritize candidate compounds, flag toxicity signals, and plan follow-up conditions
Flow Cytometry: Cell population QC
Immune cells, cell therapy, and quality control
Organize FCS gating, population ratios, and abnormal population comparisons for cell therapy, immune analysis, and reporting workflows.
- Inputs
- FCS files, panel definitions, gating conditions, sample groups
- Outputs
- Population ratios, gate-level comparisons, abnormal population candidates, QC summaries
- Decision use
- Review cell-production lots, compare immune response, and catch quality drift earlier
NGS: Integrated variant and expression review
Genomics, RNA-seq, and clinical research
Bring sequence outputs, variant candidates, expression changes, and sample context into a single review surface with other assay results.
- Inputs
- FASTQ/BAM/VCF files, expression tables, sample attributes, phenotype context
- Outputs
- Variant candidates, expression changes, annotations, cross-sample review views
- Decision use
- Shortlist genes, interpret group differences, and choose follow-up validation targets
Molecular Structure: 3D structure comparison
Proteins, materials, and structural evaluation
Manage 3D structures, segmented regions, features, and candidate models so structural differences and regions of interest are easier to compare.
- Inputs
- PDB/mmCIF files, predicted structures, binding sites, candidate molecules or materials
- Outputs
- Structure overlays, difference regions, binding-site notes, comparison reports
- Decision use
- Review structure hypotheses, compare candidates, and prepare docking or materials evaluation
MassSpec: Spectral peak interpretation
Metabolites, quality evaluation, and component comparison
Manage spectra, peaks, sample conditions, and comparison groups to support component review, quality differences, and reporting.
- Inputs
- mzML/mzXML files, peak lists, sample conditions, comparison groups or lots
- Outputs
- Peak candidates, component comparisons, quality differences, report annotations
- Decision use
- Confirm metabolite candidates, understand lot differences, and organize quality evidence