AI tools for Cell network
Related Tools:
CellProfiler
CellProfiler is an AI tool designed for biologists to analyze and process images automatically. It allows users to load image-processing modules, adjust settings, measure phenotypes, export data, and classify phenotypes using machine learning. The application is user-friendly and provides a seamless experience for biologists to analyze complex or subtle phenotypes in their images.
Deepcell
Deepcell is a company that develops technology for single-cell analysis. Their REM-I platform combines label-free imaging, deep learning, and gentle sorting to leverage single cell morphology as a high-dimensional quantitative readout. This allows researchers to gain insights into cells' phenotype and function to address important research questions across biology.
Byterat
Byterat is a cloud-based platform that provides battery data management, visualization, and analytics. It offers an end-to-end data pipeline that automatically synchronizes, processes, and visualizes materials, manufacturing, and test data from all labs. Byterat also provides 24/7 access to experiments from anywhere in the world and integrates seamlessly with current workflows. It is customizable to specific cell chemistries and allows users to build custom visualizations, dashboards, and analyses. Byterat's AI-powered battery research has been published in leading journals, and its team has pioneered a new class of models that extract tell-tale signals of battery health from electrical signals to forecast future performance.
Tablesmith
Tablesmith is a free, privacy-first, and intuitive spreadsheet automation tool that allows users to build reusable data flows, effortlessly sort, filter, group, format, or split data across files/sheets based on cell values. It is designed to be easy to learn and use, with a focus on privacy and cross-platform compatibility. Tablesmith also offers an AI autofill feature that suggests and fills in information based on the user's prompt.
Spreadsheet Daddy
Spreadsheet Daddy is an AI-powered add-on for Google Sheets that enables users to automate tasks, generate content, extract data, and perform various other functions using advanced AI models like GPT-4 and GPT-4-32k. It seamlessly integrates with Google Sheets, allowing users to leverage the power of AI within their spreadsheets. With its user-friendly interface and diverse range of features, Spreadsheet Daddy empowers businesses and individuals to enhance their productivity and efficiency.
Genie TechBio
Genie TechBio is the world's first AI bioinformatician, offering an LLM-powered omics analysis software that operates entirely in natural language, eliminating the need for coding. Researchers can effortlessly analyze extensive datasets by engaging in a conversation with Genie, receiving recommendations for analysis pipelines, and obtaining results. The tool aims to accelerate biomedical research and empower scientists with newfound data analysis capabilities.
FileDrop
FileDrop is a file or document manager that allows you to drag and drop files into a document with automatic linking and save them to Google Drive. It also offers features like OCR, translation, and AI integration. With FileDrop, you can easily insert, save, and link files in Google Sheets cells, Docs, and Slides.
Cele
Cele is a free, AI-powered gift finder that helps you find the perfect gift for everyone, every time. With Cele, you can take a short quiz about the person you want to buy a gift for, and Cele's AI will create a customized list of gifts that are personalized to you and your loved one. You can then rate, browse, stash, or purchase from the personalized gift options and start celebrating. Cele's AI has been featured on top trending gift sites and has helped users find the perfect gift for their loved ones.
AI Voice Generator
AI Voice Generator is a Telegram bot that converts text into audio using artificial intelligence. It offers a variety of neural voices, making it easy to create natural-sounding voiceovers. The bot is simple to use, and you can generate audio in seconds.
PaletteMaker
PaletteMaker is a unique tool for creative professionals and color lovers that allows you to create color palettes and test their behavior in pre-made design examples from the most common creative fields such as Logo design, UI/UX, Patterns, Posters and more. Check Color Behavior See how color works together in various of situations in graphic design. AI Color Palettes Filter palettes of different color tone and number of colors. Diverse Creative Fields Check your colors on logo, ui design, posters, illustrations and more. Create Palettes On-The-Go Instantly see the magic of creating color palettes. Totally Free PaletteMaker is created by professional designers, it’s completely free to use and forever will be. Powerful Export Export your palette in various formats, such as Procreate, Adobe ASE, Image, and even Code.
GRAIL
GRAIL is a healthcare company innovating to solve medicine’s most important challenges. Our team of leading scientists, engineers and clinicians are on an urgent mission to detect cancer early, when it is more treatable and potentially curable. GRAIL's Galleri® test is a first-of-its-kind multi-cancer early detection (MCED) test that can detect a signal shared by more than 50 cancer types and predict the tissue type or organ associated with the signal to help healthcare providers determine next steps.
SheetMagic
SheetMagic is an AI-powered tool that allows users to perform various tasks within Google Sheets, including generating AI content, web scraping, data analysis, and data preparation. It integrates with ChatGPT, allowing users to access advanced AI capabilities without coding or hiring developers. SheetMagic is designed to enhance productivity and streamline workflows for individuals and teams.
OpenAI01
OpenAI01.net is an AI tool that offers free usage with some limitations. It provides a new series of AI models designed to spend more time thinking before responding, capable of reasoning through complex tasks and solving harder problems in science, coding, and math. Users can ask questions and get answers for free, with the option to select different models based on credits. The tool excels in complex reasoning tasks and has shown impressive performance in various benchmarks.
Cell Tuber, Machine Assistant
Hello I'm Cell Tuber, Machine Assistant! What would you like help with today?
Stem Cell Regeneration Sage
Expert in biology, always ready to clarify new stem cell treatments.biomedical research, clinical trials. Learn about different stem cell types, current/future uses, and the latest in research.
SCLC Atlas
Expert in SCLC research, focused on a specific paper and broader SCLC knowledge.
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私はExcelのショートカットキーのクイズを出題するボットです。私の出した問題に正しく回答してください。採点します。
ImageJ Mentor
I assist biological image analysis, including ImageJ macro and Python coding.
Bloodwork Interpreter Pro
A professional blood test analyst providing interpretations and insights.
Microscopic Marvel
I create authentic, detailed magnified images with educational insights.
Smartphone Repair Manual
A virtual smartphone repair manual offering detailed fixing instructions.
Repair Hero
Allround electronics repair expert with practical advise and video resources on range of devices. Think circular, avoid e-waste.
PINNACLE
PINNACLE is a flexible geometric deep learning approach that trains on contextualized protein interaction networks to generate context-aware protein representations. It provides protein representations split across various cell-type contexts from different tissues and organs. The tool can be fine-tuned to study the genomic effects of drugs and nominate promising protein targets and cell-type contexts for further investigation. PINNACLE exemplifies the paradigm of incorporating context-specific effects for studying biological systems, especially the impact of disease and therapeutics.
nntrainer
NNtrainer is a software framework for training neural network models on devices with limited resources. It enables on-device fine-tuning of neural networks using user data for personalization. NNtrainer supports various machine learning algorithms and provides examples for tasks such as few-shot learning, ResNet, VGG, and product rating. It is optimized for embedded devices and utilizes CBLAS and CUBLAS for accelerated calculations. NNtrainer is open source and released under the Apache License version 2.0.
Quantus
Quantus is a toolkit designed for the evaluation of neural network explanations. It offers more than 30 metrics in 6 categories for eXplainable Artificial Intelligence (XAI) evaluation. The toolkit supports different data types (image, time-series, tabular, NLP) and models (PyTorch, TensorFlow). It provides built-in support for explanation methods like captum, tf-explain, and zennit. Quantus is under active development and aims to provide a comprehensive set of quantitative evaluation metrics for XAI methods.
Scientific-LLM-Survey
Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.
cellseg_models.pytorch
cellseg-models.pytorch is a Python library built upon PyTorch for 2D cell/nuclei instance segmentation models. It provides multi-task encoder-decoder architectures and post-processing methods for segmenting cell/nuclei instances. The library offers high-level API to define segmentation models, open-source datasets for training, flexibility to modify model components, sliding window inference, multi-GPU inference, benchmarking utilities, regularization techniques, and example notebooks for training and finetuning models with different backbones.
intro_pharma_ai
This repository serves as an educational resource for pharmaceutical and chemistry students to learn the basics of Deep Learning through a collection of Jupyter Notebooks. The content covers various topics such as Introduction to Jupyter, Python, Cheminformatics & RDKit, Linear Regression, Data Science, Linear Algebra, Neural Networks, PyTorch, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks, Autoencoders, Graph Neural Networks, and Summary. The notebooks aim to provide theoretical concepts to understand neural networks through code completion, but instructors are encouraged to supplement with their own lectures. The work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
EDA-AI
EDA-AI is a repository containing implementations of cutting-edge research papers in the field of chip design. It includes DeepPlace, PRNet, HubRouter, and PreRoutGNN models for tasks such as placement, routing, timing prediction, and global routing. Researchers and practitioners can leverage these implementations to explore advanced techniques in chip design.
learnopencv
LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.
MATLAB-Simulink-Challenge-Project-Hub
MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.
ML-AI-2-LT
ML-AI-2-LT is a repository that serves as a glossary for machine learning and deep learning concepts. It contains translations and explanations of various terms related to artificial intelligence, including definitions and notes. Users can contribute by filling issues for unclear concepts or by submitting pull requests with suggestions or additions. The repository aims to provide a comprehensive resource for understanding key terminology in the field of AI and machine learning.
Awesome-Attention-Heads
Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.
DNAnalyzer
DNAnalyzer is a nonprofit organization dedicated to revolutionizing DNA analysis through AI-powered tools. It aims to democratize access to DNA analysis for a deeper understanding of human health and disease. The tool provides innovative AI-powered analysis and interpretive tools to empower geneticists, physicians, and researchers to gain deep insights into DNA sequences, revolutionizing how we understand human health and disease.
PPTist
PPTist is a web-based presentation application that replicates most features of Microsoft Office PowerPoint. It supports various elements like text, images, shapes, charts, tables, videos, audio, and formulas. Users can edit and present slides directly in a web browser. It offers easy development with Vue 3.x and TypeScript, user-friendly experience with context menu and keyboard shortcuts, and feature-rich functionalities including AI-generated PPTs and mobile editing. PPTist aims to provide a desktop application-level experience for creating presentations.
machine-learning-research
The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.
KwaiAgents
KwaiAgents is a series of Agent-related works open-sourced by the [KwaiKEG](https://github.com/KwaiKEG) from [Kuaishou Technology](https://www.kuaishou.com/en). The open-sourced content includes: 1. **KAgentSys-Lite**: a lite version of the KAgentSys in the paper. While retaining some of the original system's functionality, KAgentSys-Lite has certain differences and limitations when compared to its full-featured counterpart, such as: (1) a more limited set of tools; (2) a lack of memory mechanisms; (3) slightly reduced performance capabilities; and (4) a different codebase, as it evolves from open-source projects like BabyAGI and Auto-GPT. Despite these modifications, KAgentSys-Lite still delivers comparable performance among numerous open-source Agent systems available. 2. **KAgentLMs**: a series of large language models with agent capabilities such as planning, reflection, and tool-use, acquired through the Meta-agent tuning proposed in the paper. 3. **KAgentInstruct**: over 200k Agent-related instructions finetuning data (partially human-edited) proposed in the paper. 4. **KAgentBench**: over 3,000 human-edited, automated evaluation data for testing Agent capabilities, with evaluation dimensions including planning, tool-use, reflection, concluding, and profiling.