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.

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.

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 Materials on this site are not peer-reviewed by arXiv.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.

Google DeepMind is an AI research lab that aims to build AI responsibly to benefit humanity. They work on complex challenges in AI, focusing on breakthrough innovations and publications. The lab has developed various AI models like Gemini, Project Astra, Imagen, Veo, AlphaFold, and SynthID. Google DeepMind emphasizes responsibility, safety, education, and career opportunities in the AI field. They are committed to making the AI ecosystem more representative of society and ensuring AI benefits the world.

Flora Incognita is an interactive plant species identification app that combines AI-supported plant identification with citizen science. Users can identify over 30,000 plant species, save observations, access extensive plant fact sheets, and contribute to scientific research. The app is free of charge, ad-free, and works offline, making it ideal for educational purposes and nature conservation initiatives.

Synthace is a software and expertise platform designed for Discovery Biology Teams to streamline and optimize their experiments in assay development, media optimization, and purification process development. The platform offers software solutions, training, and on-site support from specialists to help scientists conduct experiments more efficiently and effectively. By leveraging multifactorial methods and automation, Synthace aims to accelerate drug discovery processes and deliver faster, definitive results.

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.

TutorEva is an AI-powered homework helper and tutor designed to assist college students in various subjects. The platform leverages artificial intelligence to provide personalized learning experiences, answer questions, and offer guidance on assignments. With TutorEva, students can access academic support anytime, anywhere, making learning more efficient and effective.

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.

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.

RapidAI Research Institute is an academic institution under the RapidAI open-source organization, a non-enterprise academic institution. It serves as a platform for academic research and collaboration, providing opportunities for aspiring researchers to publish papers and engage in scholarly activities. The institute offers mentorship programs and benefits for members, including access to resources such as internet connectivity, GPU configurations, and storage space. The management team consists of esteemed professionals in the field, ensuring a conducive environment for academic growth and development.

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.

The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.

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.

Awesome-LLM is a curated list of resources related to large language models, focusing on papers, projects, frameworks, tools, tutorials, courses, opinions, and other useful resources in the field. It covers trending LLM projects, milestone papers, other papers, open LLM projects, LLM training frameworks, LLM evaluation frameworks, tools for deploying LLM, prompting libraries & tools, tutorials, courses, books, and opinions. The repository provides a comprehensive overview of the latest advancements and resources in the field of large language models.

Text2Text is a comprehensive language modeling toolkit that offers a wide range of functionalities for text processing and generation. It provides tools for tokenization, embedding, TF-IDF calculations, BM25 scoring, indexing, translation, data augmentation, distance measurement, training/finetuning models, language identification, and serving models via a web server. The toolkit is designed to be user-friendly and efficient, offering a variety of features for natural language processing tasks.

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.

The Korean SAT LLM Leaderboard is a benchmarking project that allows users to test their fine-tuned Korean language models on a 10-year dataset of the Korean College Scholastic Ability Test (CSAT). The project provides a platform to compare human academic ability with the performance of large language models (LLMs) on various question types to assess reading comprehension, critical thinking, and sentence interpretation skills. It aims to share benchmark data, utilize a reliable evaluation dataset curated by the Korea Institute for Curriculum and Evaluation, provide annual updates to prevent data leakage, and promote open-source LLM advancement for achieving top-tier performance on the Korean CSAT.

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.

SciCode is a challenging benchmark designed to evaluate the capabilities of language models (LMs) in generating code for solving realistic scientific research problems. It contains 338 subproblems decomposed from 80 challenging main problems across 16 subdomains from 6 domains. The benchmark offers optional descriptions specifying useful scientific background information and scientist-annotated gold-standard solutions and test cases for evaluation. SciCode demonstrates a realistic workflow of identifying critical science concepts and facts and transforming them into computation and simulation code, aiming to help showcase LLMs' progress towards assisting scientists and contribute to the future building and evaluation of scientific AI.

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