Our work builds upon decades of research by CASP’s organisers and the protein folding community, and we’re indebted to the countless number of people who have contributed protein structures over the years, making such rigorous evaluations possible. At CASP14 (2020), we presented our latest version of AlphaFold, which has now reached a level of accuracy considered to solve the protein structure prediction problem. Groups must submit their best predictions to see how close they are to the subsequently revealed structures.Īmong the teams that participated in CASP13 (2018), AlphaFold placed first in the protein structure prediction challenge.
Teams are given a selection of amino acid sequences for proteins which have had their exact 3D shape mapped but have not yet been released into the public domain. The community also organises a biennial challenge for research groups to test the accuracy of their predictions against real experimental data. In 1994, scientists interested in protein folding formed CASP (Critical Assessment of protein Structure Prediction).ĬASP is a community forum that allows researchers to share progress on the protein folding problem. Each one has a unique 3D shape that determines how it works and what it does.īut figuring out the exact structure of a protein remains an expensive and often time-consuming process, meaning we only know the exact 3D structure of a tiny fraction of the proteins known to science.įinding a way to close this rapidly expanding gap and predict the structure of millions of unknown proteins could not only help us tackle disease and more quickly find new medicines but perhaps also unlock the mysteries of how life itself works. They’re the building blocks of life.Ĭurrently, there are around 100 million known distinct proteins, with many more found every year. They underpin not just the biological processes in your body but every biological process in every living thing. These exquisite, intricate machines are proteins. They’re what allow your eyes to detect light, your neurons to fire, and the ‘instructions’ in your DNA to be read, which make you the unique person you are. All data is anonymized to protect user privacy.Inside every cell in your body, billions of tiny molecular machines are hard at work. Each playlist in the MPD contains a playlist title, the track list (including track IDs and metadata), and other metadata fields (last edit time, number of playlist edits, and more). The playlists were created by Spotify users between January 2010 and November 2017. Sampled from the over 2 billion public playlists on Spotify, this dataset of 1 million playlists consist of over 2 million unique tracks by nearly 300,000 artists, and represents the largest dataset of music playlists in the world. To enable this type of research at scale, earlier this year we released The Million Playlist Dataset (MPD) to the academic research community. Spotify’s “Recommended Songs” feature suggests songs to add to a playlist This can make playlist creation easier, and ultimately help people find more of the music they love. Why do certain songs go together? What is the difference between “ Beach Vibes” and “ Forest Vibes”? And what words (and emojis) do people use to describe which playlists?īy learning more about nature of playlists, we may also be able to suggest other tracks that a listener would enjoy in the context of a given playlist. By learning from the playlists that people create, we can learn all sorts of things about the deep relationship between people and music. The other thing we love here at Spotify is playlist research. I told my crush I liked them through a Spotify playlist /f51lfkIMQv focus, workout). Some playlists are even made to land a dream job, or to send a message to someone special. romantic, sad, holiday), or for a particular purpose (e.g. by genre, artist, year, or city), by mood, theme, or occasion (e.g.
People create playlists for all sorts of reasons: some playlists group together music categorically (e.g. To date, over 2 billion playlists have been created and shared by Spotify users. In fact, the Digital Music Alliance, in their 2018 Annual Music Report, state that 54% of consumers say that playlists are replacing albums in their listening habits.īut our users don’t love just listening to playlists, they also love creating them. I walked the length of my platform just to read them all /vV7LbW8zpM Playlists like Today’s Top Hits and RapCaviar have millions of loyal followers, while Discover Weekly and Daily Mix are just a couple of our personalized playlists made especially to match your unique musical tastes.īig fan of the new Spotify campaign.