DREAM (Dialogue for Reverse Engineering Assessments and Methods) poses fundamental questions about systems biology, and invites participants to propose solutions. The main objective is to catalyze the interaction between theory and experiment, specifically in the area of cellular network inference and quantitative model building. DREAM challenges address how we can assess the quality of our descriptions of networks that underlie biological systems, and of our predictions of the outcomes of novel experiments. These are not simple questions. Researchers have used a variety of algorithms to deduce the structure of biological networks and/or to predict the outcome of perturbations to their systems. They have also evaluated the success of their methodologies using a diverse set of non-standardised metrics. What is still needed, and what DREAM aims to achieve, is a fair comparison of the strengths and weaknesses of these methods and a clear sense of the reliability of the models that researchers create.

Helping scientists in developing countries to access the power of internet-based volunteer computing and volunteer thinking.

You can help marine researchers understand what whales are saying. Listen to the large sound and find the small one that matches it best. Click 'Help' below for an interactive guide.

LHC@home is a platform for volunteers to help physicists develop and exploit particle accelerators like CERN's Large Hadron Collider, and to compare theory with experiment in the search for new fundamental particles. By contributing spare processing capacity on their home and laptop computers, volunteers may run simulations of beam dynamics and particle collisions in the LHC's giant detectors

Help scientists recover worldwide weather observations made by Royal Navy ships around the time of World War I. These transcriptions will contribute to climate model projections and improve a database of weather extremes. Historians will use your work to track past ship movements and the stories of the people on board.

Help solar scientists spot explosions on the Sun and track them across space to Earth. Your work will give astronauts an early warning if dangerous solar radiation is headed their way. And you could make a new scientific discovery.

Milkyway@Home uses the BOINC platform to harness volunteered computing resources, creating a highly accurate three dimensional model of the Milky Way galaxy using data gathered by the Sloan Digital Sky Survey. This project enables research in both astroinformatics and computer science. In computer science, the project is investigating different optimization methods which are resilient to the fault-prone, heterogeneous and asynchronous nature of Internet computing; such as evolutionary and genetic algorithms, as well as asynchronous newton methods. While in astroinformatics, Milkyway@Home is generating highly accurate three dimensional models of the Sagittarius stream, which provides knowledge about how the Milky Way galaxy was formed and how tidal tails are created when galaxies merge.

A real-time, online checklist program, eBird has revolutionized the way that the birding community reports and accesses information about birds. Launched in 2002 by the Cornell Lab of Ornithology and National Audubon Society, eBird provides rich data sources for basic information on bird abundance and distribution at a variety of spatial and temporal scales. eBird's goal is to maximize the utility and accessibility of the vast numbers of bird observations made each year by recreational and professional bird watchers. It is amassing one of the largest and fastest growing biodiversity data resources in existence.

In an effort to secure mass-collaboration, the company has launched a $7 million competition to reward talented minds for their potential contribution in perfecting the Personal Genome Machine sequencer that the company has developed. The machine relies on semi-conductor technology and has the capability of transforming chemical data into digital information. It is the first of its kind in the world and creative minds can enter the Grand Challenges Contest.

The Great Sunflower Project targets bee and gardening enthusiasts to help research on a large scale what wild bees are doing and what effects there are on polination of garden plants, crops and wild plants.

BOINC harnesses the idle time of participants' computers for a massive, crowdsourced version of distributed computing. This computing power is then marshaled for and made available for virtuous scientific necessities including global warming research, planet discovery, extraterrestrial study, and more. The entities and projects utilizing the BOINC platform to crowdsource their research include SETI, FightAIDS@home, the Collatz Conjecture project and more.

The GalaxyZoo project invites collaborators to take part in an initiative to classify galaxies. By tapping the available time from thousands of gamers and avoiding the expense of labor-intensive non-specialty research, highly qualified scientists are able to focus on specialty tasks and tremendous efficiencies are achieved in terms of speed, results, and reduced research costs.

Monday, January 23, 2012 Computer Games for CrowdsourcingScientific Research Do you like computer games?If yes, here you have two options to play and at the same timecontribute to genetic and biotechnology research: phylo It looks like a game, but it is a tool to improve multiple sequencealignments of DNA regions that may be linked to various geneticdisorders. Sequence alignment is a way of identifying regions of similarity that may be consequence of functional, structural orevolutionary relationship between the sequences. This alignment isusually done with the aid of computer algorithms, however they do notguarantee a global optimization as it will take a prohibitively expensivecomputational power to achieve it.

We introduce Peekaboom, an entertaining web-based game that can help computers locate objects in images. People play the game because of its entertainment value, and as a side effect of them playing, we collect valuable image metadata, such as which pixels belong to which object in the image. The collected data could be applied towards constructing more accurate computer vision algorithms, which require massive amounts of training and testing data not currently available. Peekaboom has been played by thousands of people, some of whom have spent over 12 hours a day playing, and thus far has generated millions of data points. In addition to its purely utilitarian aspect, Peekaboom is an example of a new, emerging class of games, which not only bring people together for leisure purposes, but also exist to improve artificial intelligence. Such games appeal to a general audience, while providing answers to problems that computers cannot yet solve.

The Biotic Games project (Stanford University) enables players to interact directly with microorganisms. The game's "hardware" is a simple console which is hooked up to a lab slide. When players push buttons on the console the microorganisms on the slide react. These reactions are displayed onscreen in real-time via a microscopic camera.

EteRNA is an online game which resembles Tetris or Dr. Mario was developed by Carnegie Mellon University and Stanford University researchers to uncover principles for designing molecules of RNA, which biologists believe may be the key regulator for all cellular activity.

Foldit was founded by the University of Washington Center for Game Science in collaboration with the Baker lab. In the last decade, scientists repeatedly failed to find a solution to the structure of a protein-cutting enzyme from an AIDS-like virus. The scientists have decided to collect a group of gamers and challenged them to produce an accurate model of the enzyme: users are tasked with folding known proteins and are scored on how well they manage to accomplish this task while taking into consideration the physical properties of the molecule. In less then ten days, the gamers came up with the desired solution.

In occasion of the Haiti earthquake an European Commission's Joint Research Center team used the damage reports mapped on the Ushahidi-Haiti platform to show that this crowdsourced data can help predict the spatial distribution of structural damage in Port-au-Prince