How Artificial Intelligence will change biology
Artificial intelligence (AI) is already beginning to have a significant impact on the field of biology, and it is poised to change the field in a number of ways.
Analysis of large datasets
One major area where AI is having an impact is in the analysis of large datasets. With advances in genomics and other high-throughput technologies, there is an enormous amount of data being generated in biology, and it can be difficult for humans to make sense of it all. AI can help by using machine learning algorithms to identify patterns and relationships in the data that might not be immediately apparent to humans. This can lead to new discoveries and insights that can advance our understanding of biological systems.
Drug Discovery (e.g., AlphaFold generated protein structures)
Another area where AI is making an impact is in drug discovery. Developing new drugs is a long and costly process, and AI can help speed up the process by predicting the efficacy and safety of potential drugs, as well as identifying new targets for drug development. AI can also help researchers repurpose existing drugs for new applications, which can save time and money.
AI is also being used to improve diagnostics and personalized medicine. By analyzing large amounts of data from a patient’s genome, medical history, and other sources, AI algorithms can help doctors make more accurate diagnoses and recommend personalized treatment plans.
Here are latest AI websites which can help you in your research review process:
Consensus.app has trained and fine tuned its AI to provide better results than google scholar. It provides results along with citations and other useful information to help you pick up right resource.
Perplexity.AI is not very specific to research, however built on Generative Pre-trained Transformers, it helps in filtering larger queries to get specific results by contextual search.
Google’s DeepMind’s success since 2018 is well known for its AlphaFold model which has solved thousands of protein structures and are available for public usage. BARD from Google is partially integrated with Google Search Engine . Having got training on much larger parameters and giant resource infrastructure, it is going to prove a better assistant than existing AI models.
ChatGPT (currently version 3) from OpenAI being a very large language model, is not suitable for research as it might output wrong and results without fine-tuning. However, it is still helpful in providing overview of the research review process.
With enormous growth and development in the field of AI the tools might be helpful in the research.
Overall, AI is poised to revolutionize the field of biology, making it possible to generate and analyze data on a scale that was not previously possible, and helping researchers make new discoveries and advancements in areas like drug discovery and personalized medicine. However, there are also challenges and ethical considerations that need to be taken into account as AI is integrated into biology research and healthcare.
5. Scholarcy Article Summarizer
Scholarcy article summarizer is online based tool for providing instant article summary power by Artificial Intelligence based algorithm to assist in summarizing longer text or an article on a website. It provides interface to summarize using webpage link or by uploading your own document.
6. Litmaps App
Litmaps app is helpful in finding research gaps in your research articles using your favourite library like Mendeley, Endnote, Paperpile, or Zotero. It is easy to find the research gap from in your research and aggregating related articles for listing the gaps.