Best AI tools for< Research Biology Topics >

BioloGPT is an AI tool designed to answer biology-related questions with insights and graphs. It provides information on various topics such as maintaining a healthy gut microbiome, foods for a healthy immune system, effects of cannabis on the brain, risks of Covid-19 vaccines, and advancements in psoriasis treatment. The tool is updated daily and cites full papers to support its answers.

Science in the News is a Harvard graduate student organization with a mission to bridge the communication gap between scientists and non-scientists. It provides a platform for researchers to share their work with the wider community in an accessible and engaging way. The website features articles, podcasts, videos, and other resources on a wide range of scientific topics, including astronomy, biology, chemistry, computer science, and physics.

ScienceCast is a platform that enhances scientific papers with interactive media, providing a unique way to explore and engage with research articles in various fields such as Biology, Computer Science, Economics, Electrical Engineering, Mathematics, Physics, and more. Users can access a wide range of featured casts, including topics like cancer biology, genomics, immunology, microbiology, molecular biology, biochemistry, and bioinformatics. The platform aims to make complex scientific information more accessible and engaging for researchers and enthusiasts alike.

Jotlify is an AI-powered platform that simplifies complex research papers, making them accessible and easy to understand for students, researchers, professionals, and curious minds. It transforms dense academic content into engaging stories and insights, bridging the gap between complex research and easy understanding. With Jotlify, users can uncover stories and insights that can transform their understanding and impact various aspects of their lives.

ePlant is an advanced plant-data intelligence platform that offers remote monitoring of trees and vines health status, enabling users to easily track thousands of trees individually. The TreeTag system utilizes state-of-the-art wireless plant health monitors and AI technology to process collected data into actionable insights. It revolutionizes plant data collection and application in various sectors such as tree services, precision agriculture, and forestry. ePlant has been recognized as one of TIME's Best Inventions 2023 and is trusted by experts for its innovative approach to plant monitoring and research.

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.

arXiv.org is a free distribution service and an open-access archive for nearly 2.4 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

Insitro is a drug discovery and development company that uses machine learning and data to identify and develop new medicines. The company's platform integrates in vitro cellular data produced in its labs with human clinical data to help redefine disease. Insitro's pipeline includes wholly-owned and partnered therapeutic programs in metabolism, oncology, and neuroscience.

Flora Incognita is an AI-supported plant identification application that allows users to identify more than 16,000 plant species. It enables users to save plant observations, access extensive plant fact sheets, and contribute to science through citizen science projects. The app is free of charge, advertising-free, and can be used offline, making it ideal for educational purposes and nature conservation initiatives. The research project 'Flora Incognita++' combines AI technology with citizen science to enhance plant identification and research.

CogPrints is an electronic archive for self-archived papers in any area of Psychology, Neuroscience, and Linguistics, and many areas of Computer Science (e.g., artificial intelligence, robotics, vision, learning, speech, neural networks), Philosophy (e.g., mind, language, knowledge, science, logic), Biology (e.g., ethology, behavioral ecology, sociobiology, behavior genetics, evolutionary theory), Medicine (e.g., Psychiatry, Neurology, human genetics, Imaging), Anthropology (e.g., primatology, cognitive ethnology, archeology, paleontology), as well as any other portions of the physical, social and mathematical sciences that are pertinent to the study of cognition.

CCDS (Center for Computational & Data Sciences) is a research center at Independent University Bangladesh dedicated to artificial intelligence, data sciences, and computational science. The center has various wings focusing on AI, computational biology, physics, data science, human-computer interaction, and industry partnerships. CCDS explores the use of computation to understand nature and society, uncover hidden stories in data, and tackle complex challenges. The center collaborates with institutions like CERN and the Dunlap Institute for Astronomy and Astrophysics.

SubstrateAI is an artificial intelligence company that creates, acquires, and scales businesses in various sectors such as Health, Finance, Human Resources, and Energy. They develop products and services based on proprietary technology and are listed on stock exchanges in Spain, the UK, and the US. SubstrateAI collaborates with Subgen AI, a subsidiary providing AI solutions to companies and governments globally. The company's technology is inspired by biology and continuously evolves through the daily efforts of researchers.

The Institute for Protein Design is a research institute at the University of Washington that uses computational design to create new proteins that solve modern challenges in medicine, technology, and sustainability. The institute's research focuses on developing new protein therapeutics, vaccines, drug delivery systems, biological devices, self-assembling nanomaterials, and bioactive peptides. The institute also has a strong commitment to responsible AI development and has developed a set of principles to guide its use of AI in research.

Seamless is an AI Literature Review Tool for Scientific Research that enables users to draft literature reviews 100x faster by leveraging advanced AI technology. It allows researchers to find relevant papers and create a draft directly from an excerpt of their work. Seamless utilizes the Semantic Scholar database of scientific papers and large language models like GPT-4 to generate literature reviews in various fields such as engineering, computer science, chemistry, biology, law, medicine, pharma, and business. The tool is designed to streamline the process of literature review creation and enhance the efficiency of researchers and students.

Mindreader is an AI application that enhances client communication by leveraging personality AI. It helps users engage with client personalities better through quizzes, linguistics, and physiognomy. The application ensures success during client research and background analysis by combining psychology, biology, and AI. Mindreader's personality AI minimizes misunderstandings with key decision makers and guarantees effective client communication. It offers a proven profiling framework to identify clients' preferred communication styles, enabling users to build strong relationships effortlessly.

Google Research is a leading research organization focusing on advancing science and artificial intelligence. They conduct research in various domains such as AI/ML foundations, responsible human-centric technology, science & societal impact, computing paradigms, and algorithms & optimization. Google Research aims to create an environment for diverse research across different time scales and levels of risk, driving advancements in computer science through fundamental and applied research. They publish hundreds of research papers annually, collaborate with the academic community, and work on projects that impact technology used by billions of people worldwide.

Google Research is a team of scientists and engineers working on a wide range of topics in computer science, including artificial intelligence, machine learning, and quantum computing. Our mission is to advance the state of the art in these fields and to develop new technologies that can benefit society. We publish hundreds of research papers each year and collaborate with researchers from around the world. Our work has led to the development of many new products and services, including Google Search, Google Translate, and Google Maps.

The Google Research Blog is a platform for researchers at Google to share their latest work in artificial intelligence, machine learning, and other related fields. The blog covers a wide range of topics, from theoretical research to practical applications. The goal of the blog is to provide a forum for researchers to share their ideas and findings, and to foster collaboration between researchers at Google and around the world.

The Research Center Trustworthy Data Science and Security is a hub for interdisciplinary research focusing on building trust in artificial intelligence, machine learning, and cyber security. The center aims to develop trustworthy intelligent systems through research in trustworthy data analytics, explainable machine learning, and privacy-aware algorithms. By addressing the intersection of technological progress and social acceptance, the center seeks to enable private citizens to understand and trust technology in safety-critical applications.

Research Studio is a next-level UX research tool that helps you streamline your user research with AI-enhanced analysis. Whether you're a freelance UX designer, user researcher, or agency, Research Studio can help you get the insights you need to make better decisions about your products and services.

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.

This repository aims to promote global equality for individuals pursuing a PhD in NLP by providing resources and information on various aspects of the academic journey. It covers topics such as applying for a PhD, getting research opportunities, preparing for the job market, and succeeding in academia. The repository is actively updated and includes contributions from experts in the field.

Awesome-Colorful-LLM is a meticulously assembled anthology of vibrant multimodal research focusing on advancements propelled by large language models (LLMs) in domains such as Vision, Audio, Agent, Robotics, and Fundamental Sciences like Mathematics. The repository contains curated collections of works, datasets, benchmarks, projects, and tools related to LLMs and multimodal learning. It serves as a comprehensive resource for researchers and practitioners interested in exploring the intersection of language models and various modalities for tasks like image understanding, video pretraining, 3D modeling, document understanding, audio analysis, agent learning, robotic applications, and mathematical research.

The 'awesome-AI4MolConformation-MD' repository focuses on protein conformations and molecular dynamics using generative artificial intelligence and deep learning. It provides resources, reviews, datasets, packages, and tools related to AI-driven molecular dynamics simulations. The repository covers a wide range of topics such as neural networks potentials, force fields, AI engines/frameworks, trajectory analysis, visualization tools, and various AI-based models for protein conformational sampling. It serves as a comprehensive guide for researchers and practitioners interested in leveraging AI for studying molecular structures and dynamics.

This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.

FuseMedML is a Python framework designed to accelerate machine learning-based discovery in the medical field by promoting code reuse. It provides a flexible design concept where data is stored in a nested dictionary, allowing easy handling of multi-modality information. The framework includes components for creating custom models, loss functions, metrics, and data processing operators. Additionally, FuseMedML offers 'batteries included' key components such as fuse.data for data processing, fuse.eval for model evaluation, and fuse.dl for reusable deep learning components. It supports PyTorch and PyTorch Lightning libraries and encourages the creation of domain extensions for specific medical domains.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

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.

AITom is an open-source platform for AI-driven cellular electron cryo-tomography analysis. It is developed to process large amounts of Cryo-ET data, reconstruct, detect, classify, recover, and spatially model different cellular components using state-of-the-art machine learning approaches. The platform aims to automate cellular structure discovery and provide new insights into molecular biology and medical applications.

CAMEL is an open-source library designed for the study of autonomous and communicative agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

A collection of papers and resources about Large Language Models (LLM) for Graph Learning (Graph). Integrating LLMs with graph learning techniques to enhance performance in graph learning tasks. Categorizes approaches based on four primary paradigms and nine secondary-level categories. Valuable for research or practice in self-supervised learning for recommendation systems.

The 'Awesome LLMs Planning Reasoning' repository is a curated collection focusing on exploring the capabilities of Large Language Models (LLMs) in planning and reasoning tasks. It includes research papers, code repositories, and benchmarks that delve into innovative techniques, reasoning limitations, and standardized evaluations related to LLMs' performance in complex cognitive tasks. The repository serves as a comprehensive resource for researchers, developers, and enthusiasts interested in understanding the advancements and challenges in leveraging LLMs for planning and reasoning in real-world scenarios.

The Microsoft AI for Earth program hosts geospatial data on Azure that is important to environmental sustainability and Earth science. This repo hosts documentation and demonstration notebooks for all the data that is managed by AI for Earth. It also serves as a "staging ground" for the Planetary Computer Data Catalog.

Especialista em Biologia Geral com dados da CAPES.

Aging biology expert blending baseline knowledge with user literature

Bu program, çok çeşitli biyoloji konuları hakkında net açıklamalar sağlar. Kullanıcılar temel biyolojik kavramlardan daha karmaşık teorilere kadar her şeyi öğrenmeyi bekleyebilirler. Biyolojiyi herkes için kolay anlaşılır hale getirmek üzere tasarlanmıştır.

Questo programma fornisce spiegazioni chiare su un'ampia gamma di argomenti di biologia. Gli utenti possono imparare tutto, dai concetti biologici di base alle teorie più complesse. È stato progettato per rendere la biologia facile da capire per tutti.

Focused on groundbreaking plant biology research for agricultural, medicinal, and environmental advancements.

Expert in cancer biology

Echoes Watson & Crick, educates on DNA with depth.

Find and summarize recent papers in biology, chemistry, and biomedical sciences.

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.

Uses OpenStax Textbooks to help answer questions and teach

Chemical biology expert for literature, data viz, and coding

Generate a structured abstract for academic papers, primarily in the field of biology, adhering to a specified word count range. Simply upload your manuscript file (without the abstract) and specify the word count (for example, '200-250') to GPT.

A customized ChatGPT designed to excel in the field of synthetic biology, as a scientist, an engineer, and a business man

I assist with statistical analysis for molecular biology

Assistente de Dados de Pós-Graduação em Ciências Biológicas

Marine biologist studying and conserving ocean life, focusing on ecosystem health and climate effects.

Expert and respectful guide on aging research and its societal impacts.

生物化学领域的知识型助手，避免提供医学建议。

Unlock the secrets of DNA with 🧬GenoCode Wizard🔬! Dive into genetic analysis, decode sequences, and explore bioinformatics with ease. Perfect for researchers and students!

Especialista em teses de Zoologia no Brasil