In a groundbreaking study, researchers at the Massachusetts Institute of Technology (MIT) have developed an automated machine learning system called BioAutoMATED that can generate AI models for biology research. Led by Jim Collins, the Termeer Professor of Medical Engineering and Science, the team aims to simplify the process of building machine learning models for scientists and engineers in the field of biology. This innovative system not only selects and builds appropriate models for given datasets but also handles the laborious task of data preprocessing. By reducing the time and effort required, BioAutoMATED opens up new possibilities for researchers in the biological sciences.
Recruiting machine learning experts can be a time-consuming and costly process for science and engineering labs. Even with an expert on board, selecting the right model, formatting the dataset, and fine-tuning the model can significantly impact its performance. According to a Google course on the Foundations of Machine Learning, data preparation and transformation alone can take up to 80% of the project time. This hurdle often discourages researchers from utilizing machine learning techniques in biology.
BioAutoMATED is an automated machine learning system specifically designed for biology research. While automated machine learning (AutoML) systems are still relatively new, with most applications focused on image and text recognition, BioAutoMATED extends the capabilities of AutoML to biological sequences. This is significant because the fundamental language of biology is based on sequences such as DNA, RNA, proteins, and glycans.
One of the key advantages of BioAutoMATED is its ability to explore and build various types of supervised ML models. These include binary classification models, multi-class classification models, and regression models. By incorporating multiple tools under one umbrella, BioAutoMATED provides a larger search space than individual AutoML tools, allowing for more flexibility and accuracy in model selection.
Traditionally, conducting experiments at the intersection of biology and machine learning has been a costly endeavor. Research groups often have to invest in significant digital infrastructure and trained human resources before they can determine if their ideas are viable. BioAutoMATED aims to lower these barriers by providing researchers with the freedom to run initial experiments and assess the feasibility of further experimentation. This way, they can determine if it’s worthwhile to hire a machine learning expert to build a different model for their research.
The benefits of using BioAutoMATED are manifold. Firstly, it significantly reduces the time and effort required to build AI models for biology research. What would typically take weeks of effort can now be accomplished in just a few hours. This time-saving allows researchers to focus more on their core research objectives rather than getting caught up in the technicalities of machine learning.
Secondly, BioAutoMATED is particularly advantageous for research groups with smaller, sparser biological datasets. It can explore models that are better-suited for such datasets, as well as more complex neural networks. This versatility ensures that researchers can make the most of their available data and obtain meaningful insights.
To promote widespread adoption and collaboration, the researchers have made the code for BioAutoMATED publicly available on GitHub. They encourage others to improve upon their work and collaborate with larger communities to make BioAutoMATED a tool for all. By generating awareness and merging biological practice with fast-paced AI-ML practice, BioAutoMATED aims to advance the field of biology research.
BioAutoMATED represents a significant breakthrough in the field of biology research. By automating the process of generating AI models, this innovative system empowers scientists and engineers to leverage machine learning for their research. With its ability to select appropriate models and handle data preprocessing, BioAutoMATED streamlines the research process and reduces the barriers to entry for researchers in the biological sciences. As the field continues to evolve, the possibilities for collaboration and discovery are endless.
A: BioAutoMATED is an automated machine learning system developed by researchers at MIT for biology research. It simplifies the process of building machine learning models for scientists and engineers by automating model selection and data preprocessing.
Q: What is the goal of BioAutoMATED?
A: The goal of BioAutoMATED is to reduce the time and effort required to build AI models for biology research. It aims to make machine learning techniques more accessible to researchers in the biological sciences.
Q: How does BioAutoMATED differ from traditional machine learning approaches?
A: BioAutoMATED is an automated machine learning system specifically designed for biology research. It extends the capabilities of automated machine learning (AutoML) to biological sequences such as DNA, RNA, proteins, and glycans. It explores and builds various types of supervised ML models, providing researchers with a larger search space for model selection.
Q: What are the advantages of using BioAutoMATED?
A: BioAutoMATED significantly reduces the time and effort required to build AI models for biology research, allowing researchers to focus more on their core objectives. It is particularly advantageous for research groups with smaller, sparser biological datasets, as it can explore models better-suited for such datasets and complex neural networks.
Q: How does BioAutoMATED lower the barriers to entry for researchers?
A: BioAutoMATED allows researchers to run initial experiments and assess the feasibility of further experimentation without the need for significant digital infrastructure or trained machine learning experts. It enables researchers to determine if it’s worthwhile to invest in additional machine learning expertise for their research.
Q: Is BioAutoMATED freely available to the public?
A: Yes, the code for BioAutoMATED has been made publicly available on GitHub. The researchers encourage others to improve upon their work and collaborate to make BioAutoMATED a tool for all. They aim to promote widespread adoption and collaboration in the field of biology research.
Q: What are the potential implications of BioAutoMATED for biology research?
A: BioAutoMATED represents a significant breakthrough in biology research by automating the process of generating AI models. It empowers scientists and engineers to leverage machine learning techniques more effectively, streamlining the research process and reducing barriers to entry. It has the potential to advance the field of biology research and foster collaboration and discovery.
John Boitnott is a news anchor at ReadWrite. Boitnott has worked at TV News Anchor, print, radio and Internet companies for 25 years. He’s an advisor at StartupGrind and has written for BusinessInsider, Fortune, NBC, Fast Company, Inc., Entrepreneur and Venturebeat. You can see his latest work on his blog, John Boitnott
NAIROBI, Kenya (AP) — The body of Ugandan Olympic athlete Rebecca Cheptegei — who died after being set on fire by her partner in Kenya — was received Friday by family and anti-femicide crusaders, ahead of her burial a day later.
Cheptegei’s family met with dozens of activists Friday who had marched to the Moi Teaching and Referral Hospital’s morgue in the western city of Eldoret while chanting anti-femicide slogans.
She is the fourth female athlete to have been killed by her partner in Kenya in yet another case of gender-based violence in recent years.
Viola Cheptoo, the founder of Tirop Angels – an organization that was formed in honor of athlete Agnes Tirop, who was stabbed to death in 2021, said stakeholders need to ensure this is the last death of an athlete due to gender-based violence.
“We are here to say that enough is enough, we are tired of burying our sisters due to GBV,” she said.
It was a somber mood at the morgue as athletes and family members viewed Cheptegei’s body which sustained 80% of burns after she was doused with gasoline by her partner Dickson Ndiema. Ndiema sustained 30% burns on his body and later succumbed.
Ndiema and Cheptegei were said to have quarreled over a piece of land that the athlete bought in Kenya, according to a report filed by the local chief.
Cheptegei competed in the women’s marathon at the Paris Olympics less than a month before the attack. She finished in 44th place.
Cheptegei’s father, Joseph, said that the body will make a brief stop at their home in the Endebess area before proceeding to Bukwo in eastern Uganda for a night vigil and burial on Saturday.
“We are in the final part of giving my daughter the last respect,” a visibly distraught Joseph said.
He told reporters last week that Ndiema was stalking and threatening Cheptegei and the family had informed police.
Four in 10 women or an estimated 41% of dating or married Kenyan women have experienced physical or sexual violence perpetrated by their current or most recent partner, according to the Kenya Demographic and Health Survey 2022.
TEL AVIV, Israel (AP) — A rare Bronze-Era jar accidentally smashed by a 4-year-old visiting a museum was back on display Wednesday after restoration experts were able to carefully piece the artifact back together.
Last month, a family from northern Israel was visiting the museum when their youngest son tipped over the jar, which smashed into pieces.
Alex Geller, the boy’s father, said his son — the youngest of three — is exceptionally curious, and that the moment he heard the crash, “please let that not be my child” was the first thought that raced through his head.
The jar has been on display at the Hecht Museum in Haifa for 35 years. It was one of the only containers of its size and from that period still complete when it was discovered.
The Bronze Age jar is one of many artifacts exhibited out in the open, part of the Hecht Museum’s vision of letting visitors explore history without glass barriers, said Inbal Rivlin, the director of the museum, which is associated with Haifa University in northern Israel.
It was likely used to hold wine or oil, and dates back to between 2200 and 1500 B.C.
Rivlin and the museum decided to turn the moment, which captured international attention, into a teaching moment, inviting the Geller family back for a special visit and hands-on activity to illustrate the restoration process.
Rivlin added that the incident provided a welcome distraction from the ongoing war in Gaza. “Well, he’s just a kid. So I think that somehow it touches the heart of the people in Israel and around the world,“ said Rivlin.
Roee Shafir, a restoration expert at the museum, said the repairs would be fairly simple, as the pieces were from a single, complete jar. Archaeologists often face the more daunting task of sifting through piles of shards from multiple objects and trying to piece them together.
Experts used 3D technology, hi-resolution videos, and special glue to painstakingly reconstruct the large jar.
Less than two weeks after it broke, the jar went back on display at the museum. The gluing process left small hairline cracks, and a few pieces are missing, but the jar’s impressive size remains.
The only noticeable difference in the exhibit was a new sign reading “please don’t touch.”
VICTORIA – The British Columbia government is partnering with a bear welfare group to reduce the number of bears being euthanized in the province.
Nicholas Scapillati, executive director of Grizzly Bear Foundation, said Monday that it comes after months-long discussions with the province on how to protect bears, with the goal to give the animals a “better and second chance at life in the wild.”
Scapillati said what’s exciting about the project is that the government is open to working with outside experts and the public.
“So, they’ll be working through Indigenous knowledge and scientific understanding, bringing in the latest techniques and training expertise from leading experts,” he said in an interview.
B.C. government data show conservation officers destroyed 603 black bears and 23 grizzly bears in 2023, while 154 black bears were killed by officers in the first six months of this year.
Scapillati said the group will publish a report with recommendations by next spring, while an independent oversight committee will be set up to review all bear encounters with conservation officers to provide advice to the government.
Environment Minister George Heyman said in a statement that they are looking for new ways to ensure conservation officers “have the trust of the communities they serve,” and the panel will make recommendations to enhance officer training and improve policies.
Lesley Fox, with the wildlife protection group The Fur-Bearers, said they’ve been calling for such a committee for decades.
“This move demonstrates the government is listening,” said Fox. “I suspect, because of the impending election, their listening skills are potentially a little sharper than they normally are.”
Fox said the partnership came from “a place of long frustration” as provincial conservation officers kill more than 500 black bears every year on average, and the public is “no longer tolerating this kind of approach.”
“I think that the conservation officer service and the B.C. government are aware they need to change, and certainly the public has been asking for it,” said Fox.
Fox said there’s a lot of optimism about the new partnership, but, as with any government, there will likely be a lot of red tape to get through.
“I think speed is going to be important, whether or not the committee has the ability to make change and make change relatively quickly without having to study an issue to death, ” said Fox.
This report by The Canadian Press was first published Sept. 9, 2024.
