Best AI tools for< Biology Tutor >

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.

The website offers online tutoring services with the help of artificial intelligence in various languages such as German, English, Croatian, Polish, Turkish, Ukrainian, and Arabic. It provides personalized tutoring sessions, homework assistance, and explanations for a wide range of school subjects. The AI tool supports self-directed learning by adapting to the user's school level and learning progress. Users can receive help in over 30 school subjects, including math, geography, history, biology, chemistry, and more. The platform allows users to upload homework assignments, receive detailed explanations, and interact with AI tutors through chat sessions.

Knowee is an AI-powered web application that provides 24/7 homework help, AI tutoring, and course notes. It offers high accuracy answers surpassing GPT-4 for various academic tasks. Users can upload images or drag and drop questions for assistance, get step-by-step solutions, and master diagrams. Knowee helps students review tough concepts, explore relevant questions, and enhance their grades across all subjects.

Gauth is an AI-powered homework helper that provides step-by-step solutions to STEM problems. It utilizes advanced algorithms and AI technology to solve complex math, statistics, calculus, physics, chemistry, biology, and history questions. Gauth also offers live expert support, with thousands of real experts available 24/7 to provide detailed explanations and guidance. The app is designed to help students of all grades and levels conquer challenging homework problems and improve their understanding of STEM subjects.

The Worksheet Generator is a free online tool that allows users to create custom printable worksheets for various subjects and grade levels. Users can generate worksheets for English, Mathematics, Science, History, Geography, Literature, Physics, Chemistry, and Biology. The tool offers a wide range of question types such as multiple choice, fill in the blanks, true/false, and open-ended questions. It is designed to be user-friendly, fast, and secure, catering to the needs of educators and students alike.

HomeworkAI is an AI-powered homework helper that provides step-by-step solutions to students and educational professionals of all levels. With HomeworkAI, users can upload their homework assignments, practice questions, or type in their questions to receive instant and accurate answers. HomeworkAI covers a wide range of subjects, including mathematics, physics, biology, chemistry, literature, and history. The platform is easy to use and provides clear and concise solutions, making it a valuable tool for students looking to improve their grades and understanding of the subject matter.

Math Sniper is an AI-powered application designed to provide precise math solutions, exam preparation assistance, and exploration of mathematical concepts. The app offers step-by-step solutions to math challenges at all levels, connects users with math tutors for personalized help, and covers a wide range of subjects beyond mathematics, such as biology, chemistry, physics, history, economics, and language tasks. With features like Snap & Ask for instant answers, step-by-step explanations, and a user-friendly interface, Math Sniper aims to enhance users' understanding of complex concepts and facilitate learning in various disciplines.

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.

Recursion is a techbio company that uses artificial intelligence to accelerate drug discovery. The company's platform combines hardware, software, and data to create a more efficient and effective drug discovery process. Recursion has a broad pipeline of drug candidates in development, and it has partnered with several leading pharmaceutical companies. The company is headquartered in Salt Lake City, Utah.

Cleerly is a digital healthcare company transforming the way clinicians approach the treatment of heart disease. Our clinically-proven, AI-based digital care platform works with coronary computed tomography angiography (CCTA) imaging to help clinicians precisely identify and define atherosclerosis earlier, so they can provide personalized, life-saving treatment plans for all patients throughout their care continuum. We measure atherosclerosis - plaque build-up in the heart's arteries - not indirect markers such as risk factors and symptoms of disease. Our AI-enabled digital care pathway offers simpler, faster, more accurate heart disease evaluation and reporting that's tailored to each stakeholder, improving overall clinical and financial outcomes.

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.

Deep Genomics is a company that uses artificial intelligence (AI) to develop RNA therapies for genetic diseases. The company's AI platform is designed to identify novel targets and evaluate thousands of possibilities to identify the best therapeutic candidates. Deep Genomics is currently developing BigRNA+, which will expand the number of mechanisms and genetic variants the company can pursue.

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 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.

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.

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.

Valo is a company that uses AI-driven technology to transform the discovery and development of life-changing medicines. They combine machine learning, tissue biology, and patient data to create a suite of powerful capabilities that bring the future of drug discovery and development to bear. Valo's team of software engineers, data scientists, biologists, medicinal chemists, and big-picture thinkers are dedicated to advancing the combined power of technology and patient data.

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.

Owkin is a full-stack AI biotech company that integrates the best of human and artificial intelligence to deliver better drugs and diagnostics at scale. By understanding complex biology through AI, Owkin identifies new treatments, de-risks and accelerates clinical trials, and builds diagnostic tools to reduce time to impact for patients.

ScienceCast is a platform that enhances scientific papers with interactive media, providing a unique way to explore research findings. Users can create and explore casts in various fields such as Biology, Computer Science, Economics, and more. The platform collaborates with arXiv Labs and is supported by NASA, offering a range of featured casts for in-depth analysis and learning.

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.

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.

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.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

ceLLama is a streamlined automation pipeline for cell type annotations using large-language models (LLMs). It operates locally to ensure privacy, provides comprehensive analysis by considering negative genes, offers efficient processing speed, and generates customized reports. Ideal for quick and preliminary cell type checks.

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.

The Octopus-v4 project aims to build the world's largest graph of language models, integrating specialized models and training Octopus models to connect nodes efficiently. The project focuses on identifying, training, and connecting specialized models. The repository includes scripts for running the Octopus v4 model, methods for managing the graph, training code for specialized models, and inference code. Environment setup instructions are provided for Linux with NVIDIA GPU. The Octopus v4 model helps users find suitable models for tasks and reformats queries for effective processing. The project leverages Language Large Models for various domains and provides benchmark results. Users are encouraged to train and add specialized models following recommended procedures.

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.

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".

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.

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 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.

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.

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.

Your personal biology coach, making CLEP prep efficient, enjoyable, and insightful.

Ein deutscher Biologietutor, geduldig und sachkundig, der Schülern beim Lernen hilft.

Genetics lecturer GPT with extensive, reviewed course materials for in-depth teaching.

Guides, quizzes, and explains concepts in NEET subjects.

Learn about any subject in a simple way, from quantum physics to the history of Egypt.

Expert in cancer biology

A biology expert, informative and scientifically accurate.

Uses OpenStax Textbooks to help answer questions and teach

A GPT based on the Swedish curriculum in Biology

Aging biology expert blending baseline knowledge with user literature

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

Chemical biology expert for literature, data viz, and coding

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.

Expert in reptile biology and conservation, informative and herpetological in tone.

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

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

Edits texts in physics and biology with scholarly precision

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.

I assist with statistical analysis for molecular biology

Expert on elephants, discussing their biology, conservation, and cultural significance.