How to Start Asking Questions

1. Product Overview

MatwingsVenus™ is an intelligent research assistant designed for scientific researchers. It replaces inefficient workflows such as reading literature word by word, manually organizing data, and repeatedly searching for information. With cross-domain information integration and structured output capabilities, it can compress a research task that originally takes one day into 30 minutes, and is widely applicable to multidisciplinary research needs in biology, materials science, medicine, and more.

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2. Intelligent Assistant

2.1 Functional Positioning

  • Core Capability: As a general-purpose research assistant, it focuses on cross-domain information processing, deep text analysis, and academic literature reasoning. Its key strengths lie in long-text comprehension and multi-source information extraction, with the ability to automatically call literature, patents, and design tools.

  • Use Cases: Cross-domain research information retrieval and integration, rapid literature review, multi-source scientific data mining (literature / patents / protein data, etc.), and logical analysis of long-form content.

  • Core Value: Reduces manual information filtering and integration costs, improves efficiency in cross-domain research, and helps quickly identify key academic insights.

2.2 Basic Operation Guide

  • Attachment Upload: Click the "📎" icon on the left side of the input box to upload PDFs or input a DOI

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  • Access Method: The default page is the intelligent assistant chat interface. You can also return to this page by deselecting any active agent module.

access method

2.3 Use Cases

2.3.1 In-depth Literature Analysis and Data Mining

2.3.1.1 Literature Analysis

  • Input Requirement: Upload the file and specify your analysis goal

I am interested in this document. Please analyze it in depth.

Reference Link

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The assistant automatically extracts key information and generates a structured overview including research background, core questions, and analytical tables

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The generated overview of the document can be seen.

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2.3.1.2 Data Mining

  • Input Requirement: Based on the generated overview, ask follow-up questions for deeper insights

What experiments were conducted? What are the key data?

Reference Link

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The assistant converts scattered descriptions into structured experiment lists and key data tables

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Truncated. Click the reference link above for full details

Although the assistant cannot extract experiment images, it can still output structured experiment and data summaries.

2.3.3 Experiment Reproduction and Visualization

  • Input Requirement: Upload experimental protocols and request reproduction and visualization

I want to reproduce the experiment in this file. What should I do? Provide a diagram.

Reference Link

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The assistant extracts key steps

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It converts complex descriptions into a clear experimental workflow diagram

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2.3.4 New Technology Analysis

  • Input Requirement: Enter a new technology and specify analysis focus

Introduce the new technology "Freeze-Cast Collagen Scaffold"

Reference Link

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The assistant generates a comprehensive report covering principles, advantages, and applications.

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2.3.5 Online Search

  • Input Requirement: Enter a cross-domain research query

Find recent literature on thermostable hydrolases, extract the best-performing sequences, and predict solubility and subcellular localization

Reference Link

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The assistant integrates literature, patents, and protein databases.

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Outputs structured research insights

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2.3.6 Structure Prediction

  • Input Requirement: Provide FASTA sequence, UniProt ID, or PDB ID

>Protein_Target_01

METVVITGASSGVGLYTARELAKRGWHVVIACRDRKLAEAAKRLGADYVVI

Reference Link

Please do not navigate to the homepage from this link

Click to view predicted 3D structure

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The system predicts structures based on input sequences and provides interactive results

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You can download the predicted PDB file

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3. Mode Selection

The platform provides three working modes for different research needs:

  • Fast Mode: Lightweight intelligent retrieval with efficient output

  • Thinking Mode: Handles complex tasks with deeper reasoning and integration

  • Thinking Mode Pro: Advanced reasoning and knowledge integration for complex cross-domain problems

4. Appendix

  1. DOI: Unique identifier for publications

  2. FASTA Format: Standard biological sequence format

  3. UniProt ID: Protein identifier

  4. PDB ID: Structure identifier

  5. ESMFold: Protein structure prediction model

  6. LDDT: Structure confidence metric

  7. XRM: X-ray microscopy

  8. AFM: Atomic force microscopy

  9. LC-MS/MS: Protein analysis technique

  10. Freeze Casting: Porous material fabrication method

  11. iPSC: Induced pluripotent stem cells

  12. Dopaminergic Neurons: Dopamine-secreting neurons

  13. GH Family: Glycoside hydrolases

  14. Non-classical Mineralization: Biomineralization pathway

  15. Proteomics: Study of proteins

  16. HAp: Hydroxyapatite

Platform design and commercial copyright belong to Tianwu