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Go from assay to insights quickly and reliably with ImageXpress imaging systems and IN Carta software

IN Carta® Image Analysis Software solves complex image analysis problems utilizing advanced Artificial Intelligence (AI) transforming images into results, which can be interpreted with ease. User-friendly workflows help you get answers faster from 2D, 3D, and 4D experiments. With the integration of our Custom Module Editor application, you can define highly customized image analysis protocols allowing you to obtain robust results—even for complex assays—then quickly visualize, review, and interact with the analysis results. Let IN Carta software do the heavy lifting so you can focus on your research.

  • Powerful Icon

    Powerful

    Guided workflows and scalable batch processing increase productivity and reduce time to answer. Experiments can be set up quickly and analysis of multiple wells is run in parallel.

  • Academia Icon

    Insightful

    Machine learning helps you leverage more information and increase accuracy in the analysis of high-content screening data to enable new discoveries with confidence.

  • Innovation Icon

    Intuitive

    Modern user experience and cutting-edge technology minimizes the software learning curve and removes barriers to productivity.

IN Carta Image Analysis Software

IN Carta Image Analysis Software

Features

  • Learning Icon

    Deep learning

    Improve specificity of your image analysis workflows by utilizing the SINAP module. SINAP relies on deep learning-based image analysis, resulting in robust segmentation for virtually any biological structure.

  • Protocols Icon

    Focused worklists

    Browse to a parent directory and populate your worklist with image datasets of interest or use search to locate a dataset of interest.

  • AI Powered Icon

    AI-powered data analytics

    Leverage the power of machine learning without being a data scientist. Identify and quantify phenotypic changes in a user-friendly workflow. Explore your data and reveal insights from complex datasets. Find novel and unexpected phenotypes with a few mouse clicks.

  • Customization Icon

    Customization

    Browse and review images from experiments, create image analysis protocols of different complexity and add on-demand data classification. Visualize analysis results using 360 ̊ data linking among images, data table and charts.

  • 3D Analysis Icon

    3D analysis

    The Custom Module Editor’s 3D application provides unprecedented flexibility in segmenting complex biological structures. Image datasets can be acquired in 3D or 4D (timelapse 3D) and tailored image analysis routines can be developed within a guided workflow.

  • Batch Analysis Icon

    Batch analysis and monitoring

    Analyze multiple experiments in batch analysis mode with one or more analysis protocols. Monitor the status of all submitted tasks and oversee their progression in real time.

IN Carta SINAP

SINAP is a module that uses deep learning algorithms to improve accuracy and reliability of high-content screening assays at the first step in the analysis pipeline—segmentation. It provides better object detection than traditional image analysis methods. Deep learning models can be easily tailored within a user-friendly tool, so that any novel biological objects can be segmented efficiently. Quantitative information extracted from segmented objects is more accurate, so errors are not propagated down the analysis pipeline.

With SINAP, Segmentation Is Not A Problem!

  • Accurate – deep learning can maintain accuracy across difficult to segment samples including confluent cells, low signal-to-noise samples and transmitted light images
  • Reliable – SINAP models can account for high phenotypic variability
  • Flexible – a single workflow can deal with a variety of applications and imaging modalities
  • Accessible – trained model learns to segment from scientist’s drawing on the image rather than asking a deep-learning guru to create a new model and optimize multiple parameters
IN Carta SINAP
Customized SINAP deep-learning models segment specific regions (whole body, head, eyes, brain) of a zebrafish embryo in transmitted light image. Courtesy of Guo Lab, UCSF

IN Carta Phenoglyphs

IN Carta® Phenoglyphs™ Software Module uses a unique combination of unsupervised and supervised machine learning to quantify phenotypical changes. Using many hundreds of cellular features that can be analyzed simultaneously, a comprehensive phenotypic profile is created and can be applied throughout an entire screening workflow. This multivariate approach to classification provides accurate characterization of object populations allowing users to resolve subtle phenotypic changes induced by drug treatment or genetic modification. It can be utilized across many biological targets including organoids, cells, spheroids, and more.

IN Carta Phenoglyphs
Classification of spheroids formed from HCT116 cells. Spheroids were stained with Hoechst 33342 to visualize nuclei. 3D stacks were collected over time.
  • Comprehensive – a data driven approach that starts with an unsupervised clustering to find patterns in the data and highlight subpopulations without prior knowledge of what phenotypes may exist.
  • Robust – dedicated machine learning algorithm identifies the optimal set of descriptive features to avoid overfitting of the resulting classification model.
  • Optimized workflow – classification is achieved by simply confirming or correcting the algorithm’s predictions until it learns the right behavior.

IN Carta Custom Module Editor 2D and 3D

  • Create simple step-by-step custom analysis
  • Tailor object segmentation and classification
  • Find objects localized within defined biological compartments
  • Report only measurements required for an assay of interest
  • Analyze live imaging data
  • True 3D segmentation (3D application only)
  • Robust reconstruction of 2D segmentation into volume for 3D assays (3D application only)

IN Carta Custom Module Editor 2D and 3D

 

Example segmentation of iPSC-derived hepatocyte spheroids in Custom Module Editor

ImageXpress® Confocal HT.ai High-Content Imaging System

Powerful multi-laser light sources, a deep tissue penetrating confocal disk module, water immersion objectives and modern machine learning analysis software

New TagImagexpress confocal

  • Ideal for highly complex cell-based and 3D assays
  • Seven-channel high-intensity lasers generating brighter images with higher signal-to-background ratio
  • Spinning confocal disk technology for deeper tissue penetration, resulting in sharper images with improved resolution
  • Water immersion objectives offering up to quadruple the signal at lower exposure times for greater sensitivity and image clarity
  • View product

StratoMineR Advanced Cloud-Based Analytics

Generate clear, deep data from complex datasets

StratoMineR Advanced Cloud-Based Analytics

Powerful and intuitive workflows allow users to port high-content imaging data directly into StratoMineR where it is used to generate rich, interactive visualizations using advanced data mining methods. When used with IN Carta Image Analysis Software, it provides robust, quantitative results from complex biological images and datasets utilizing advanced AI technology. Use all of your high-content data to discover, characterize, and analyze Phenotypes.

Latest Resources

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  • Live Cell Imaging

    Live Cell Imaging

    Live cell imaging is the study of cellular structure and function in living cells via microscopy. It enables the visualization and quantitation of dynamic cellular processes in real time. Live cell imaging encompasses a broad range of topics and biological applications—whether it is performing long-term kinetic assays or fluorescently labeling live cells.

    Learn More  

Resources of IN Carta Image Analysis Software

Presentations
Videos & Webinars
Streamline your end-to-end Cell Painting workflow

3D Imaging Seminar Series

Organoid Culture and Image-Based Analyses

New standard in organoid culture and image-based analyses

Automate your 3D biology high-throughput workflows

Automate your 3D biology high-throughput workflows

Leverage automated, end-to-end workflows to enable complex organoid assays

Level Up your 3D Cell Culture

Level Up your 3D Cell Culture: From Research to High-Throughput

Enhance high-content 3D biology

Enhance high-content 3D biology imaging with automated sample preparation

Enhancing 3D Disease Models

Enhancing 3D Disease Models: Automated, High-Throughput, Phenotypic Screening with Organ-on-a-Chip

High-Content Phenotypic Screening

High-Content Phenotypic Screening

Emerging Organoid Models

Emerging Organoid Models: Translating Basic Research to Drug Development and Regenerative Medicine

Automating culture and high-content imaging

Automating culture and high-content imaging of 3D organoids for in vitro assessment of compound effects

Deep Learning-Based Image Analysis

Deep Learning-Based Image Analysis for Label-Free Live Monitoring of iPSC and 3D Organoid Cultures

Monitoring organoid development in iPSC-derived 3D cerebral

Monitoring organoid development in iPSC-derived 3D cerebral organoids

Automated Culture and High-Content Imaging of 3D Lung

ISSCR 2021 Innovation Showcase: Automated Culture and High-Content Imaging of 3D Lung and Cardiac

  • Citation
    Dated: May 16, 2022
    Publication Name: Aging

    Senescence-associated morphological profiles (SAMPs): an image-based phenotypic profiling method for evaluating the inter and intra model heterogeneity of senescence

    Senescence occurs in response to a number of damaging stimuli to limit oncogenic transformation and cancer development. As no single, universal senescence marker has been discovered, the confident classification of senescence induction requires the parallel assessment of a series of hallmarks. Therefore, there is a growing need for “first-pass”… View more

    Senescence occurs in response to a number of damaging stimuli to limit oncogenic transformation and cancer development. As no single, universal senescence marker has been discovered, the confident classification of senescence induction requires the parallel assessment of a series of hallmarks. Therefore, there is a growing need for “first-pass” tools of senescence identification to streamline experimental workflows and complement conventional markers.

    Contributors: Ryan Wallis, Deborah Milligan, Bethany Hughes, Hannah Mizen, José Alberto López-Domínguez, Ugochim Eduputa, Eleanor J. Tyler, Manuel Serrano, Cleo L. Bishop  
    Go to article

  • Citation
    Dated: Feb 01, 2022
    Publication Name: ScienceDirect

    Virtual screening and in vitro validation of natural compound inhibitors against SARS-CoV-2 spike protein

    The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to a major public health burden and has resulted in millions of deaths worldwide. As effective treatments are limited, there is a significant requirement for high-throughput, low resource methods for the discovery of novel antivirals. The SARS-CoV-2 spike protein plays a key role in… View more

    The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to a major public health burden and has resulted in millions of deaths worldwide. As effective treatments are limited, there is a significant requirement for high-throughput, low resource methods for the discovery of novel antivirals. The SARS-CoV-2 spike protein plays a key role in viral entry and has been identified as a therapeutic target.

    Contributors: Helen Power, Jiadai Wu, Stuart Turville, Anupriya Aggarwal, Peter Valtchev, Aaron Schindeler, Fariba Dehghani  
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  • Citation
    Dated: Nov 03, 2021
    Publication Name: American Chemical Society

    Potent Anti-SARS-CoV-2 Activity by the Natural Product Gallinamide A and Analogues via Inhibition of Cathepsin L

    Cathepsin L is a key host cysteine protease utilized by coronaviruses for cell entry and is a promising drug target for novel antivirals against SARS-CoV-2. The marine natural product gallinamide A and several synthetic analogues were identified as potent inhibitors of cathepsin L with IC50 values in the picomolar range. Lead molecules possessed… View more

    Cathepsin L is a key host cysteine protease utilized by coronaviruses for cell entry and is a promising drug target for novel antivirals against SARS-CoV-2. The marine natural product gallinamide A and several synthetic analogues were identified as potent inhibitors of cathepsin L with IC50 values in the picomolar range. Lead molecules possessed selectivity over other cathepsins and alternative host proteases involved in viral entry. Gallinamide A directly interacted with cathepsin L in cells and, together with two lead analogues, potently inhibited SARS-CoV-2 infection in vitro, with EC50 values in the nanomolar range. Reduced antiviral activity was observed in cells overexpressing transmembrane protease, serine 2 (TMPRSS2); however, a synergistic improvement in antiviral activity was achieved when combined with a TMPRSS2 inhibitor. These data highlight the potential of cathepsin L as a COVID-19 drug target as well as the likely need to inhibit multiple routes of viral entry to achieve efficacy.

    Contributors: Anneliese S. Ashhurst, Arthur H. Tang, Pavla Fajtová, Michael C. Yoon, Anupriya Aggarwal, Max J. Bedding, Alexander Stoye, Laura Beretta, Dustin Pwee, Aleksandra Drelich, Danielle Skinner, Linfeng Li, Thomas D. Meek, James H. McKerrow, Vivian Hook, Chien-Te Tseng, Mark Larance, Stuart Turville, William H. Gerwick*, Anthony J. O’Donoghue*, and Richard J. Payne*  
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  • Citation
    Dated: Nov 01, 2021
    Publication Name: AAN PUBLICATIONS

    GRP78 Antibodies Are Associated With Blood-Brain Barrier Breakdown in Anti–Myelin Oligodendrocyte Glycoprotein Antibody–Associated Disorder

    To analyze (1) the effect of immunoglobulin G (IgG) from patients with anti–myelin oligodendrocyte glycoprotein antibody (MOG-Ab)–associated disorder on the blood-brain barrier (BBB) endothelial cells and (2) the positivity of glucose-regulated protein 78 (GRP78) antibodies in MOG-Ab–associated disorders. View more

    To analyze (1) the effect of immunoglobulin G (IgG) from patients with anti–myelin oligodendrocyte glycoprotein antibody (MOG-Ab)–associated disorder on the blood-brain barrier (BBB) endothelial cells and (2) the positivity of glucose-regulated protein 78 (GRP78) antibodies in MOG-Ab–associated disorders.

    Contributors: Fumitaka Shimizu, Ryo Ogawa, Yoichi Mizukami, Kenji Watanabe, Kanako Hara, Chihiro Kadono, Toshiyuki Takahashi, View ORCID ProfileTatsuro Misu, Yukio Takeshita, Yasuteru Sano, Miwako Fujisawa, Toshihiko Maeda, View ORCID ProfileIchiro Nakashima, Kazuo Fujihara, Takashi Kanda  
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  • Citation
    Dated: Sep 24, 2021
    Publication Name: ScienceDirect

    Immunisation of ferrets and mice with recombinant SARS-CoV-2 spike protein formulated with Advax-SM adjuvant protects against COVID-19 infection

    The development of a safe and effective vaccine is a key requirement to overcoming the COVID-19 pandemic. Recombinant proteins represent the most reliable and safe vaccine approach but generally require a suitable adjuvant for robust and durable immunity. We used the SARS-CoV-2 genomic sequence and in silico structural modelling to design a… View more

    The development of a safe and effective vaccine is a key requirement to overcoming the COVID-19 pandemic. Recombinant proteins represent the most reliable and safe vaccine approach but generally require a suitable adjuvant for robust and durable immunity. We used the SARS-CoV-2 genomic sequence and in silico structural modelling to design a recombinant spike protein vaccine (Covax-19).

    Contributors: LeiLia, Yoshikazu Honda-Okubo, Ying Huang, HyesunJang, Michael A. Carlock, Jeremy Baldwin, Sakshi Piplani, Anne G.Bebin-Blackwell, DavidForgacs, Kaori Sakamoto, Alberto Stella, Stuart Turville, Tim Chataway, Alex Colella, Jamie Triccas, Ted M. Ross, Nikolai Petrovsky  
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  • Citation
    Dated: Apr 20, 2021
    Publication Name: ScienceDirect

    Long-term persistence of RBD+ memory B cells encoding neutralizing antibodies in SARS-CoV-2 infection

    Considerable concerns relating to the duration of protective immunity against severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) exist, with evidence of antibody titers declining rapidly after infection and reports of reinfection. Here, we monitor the antibody responses against SARS-CoV-2 receptor-binding domain (RBD) for up to 6 months… View more

    Considerable concerns relating to the duration of protective immunity against severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) exist, with evidence of antibody titers declining rapidly after infection and reports of reinfection. Here, we monitor the antibody responses against SARS-CoV-2 receptor-binding domain (RBD) for up to 6 months after infection. While antibody titers are maintained, ∼13% of the cohort’s neutralizing responses return to background.

    Contributors: Arunasingam Abayasingam, Harikrishnan Balachandran, David Agapiou, Mohamed Hammoud, Chaturaka Rodrigo, Elizabeth Keoshkerian, Hui Li, Nicholas A. Brasher, Daniel Christ, Romain Rouet, Deborah Burnet, Branka Grubor-Bauk, William Rawlinson, StuartTurville, Anupriya Aggarwal, Alberto Ospina Stella, Christina Fichter, Fabienne Brilot…Rowena A. Bull  
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Explore our high-content imaging portfolio

High-content imaging and analysis solutions, ranging from automated digital microscopy to high-throughput confocal imaging systems with water immersion objectives and proprietary spinning disk technology.