Google-AAD syllabus is available at

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Exam Code: Google-AAD Practice test 2022 by team
Google-AAD Google Associate Android Developer

Exam Number: Google-AAD
Exam Name : Google Associate Android Developer


The test is designed to test the skills of an entry-level Android developer. Therefore, to take this exam, you should have this level of proficiency, either through education, self-study, your current job, or a job you have had in the past. Assess your proficiency by reviewing "Exam Content." If you'd like to take the exam, but feel you need to prepare a bit more, level up your Android knowledge with some great Android training resources.

Android core
User interface
Data management

Android core

To prepare for the Associate Android Developer certification exam, developers should:
Understand the architecture of the Android system
Be able to describe the basic building blocks of an Android app
Know how to build and run an Android app
Display simple messages in a popup using a Toast or a Snackbar
Be able to display a message outside your app's UI using Notifications
Understand how to localize an app
Be able to schedule a background task using WorkManager

User interface

The Android framework enables developers to create useful apps with effective user interface (UIs). Developers need to understand Android’s activities, views, and layouts to create appealing and intuitive UIs for their users.

To prepare for the Associate Android Developer certification exam, developers should:
Understand the Android activity lifecycle
Be able to create an Activity that displays a Layout
Be able to construct a UI with ConstraintLayout
Understand how to create a custom View class and add it to a Layout
Know how to implement a custom app theme
Be able to add accessibility hooks to a custom View
Know how to apply content descriptions to views for accessibility
Understand how to display items in a RecyclerView
Be able to bind local data to a RecyclerView list using the Paging library
Know how to implement menu-based navigation
Understand how to implement drawer navigation

Data management

Many Android apps store and retrieve user information that persists beyond the life of the app.

To prepare for the Associate Android Developer certification exam, developers should:
Understand how to define data using Room entities
Be able to access Room database with data access object (DAO)
Know how to observe and respond to changing data using LiveData
Understand how to use a Repository to mediate data operations
Be able to read and parse raw resources or asset files
Be able to create persistent Preference data from user input
Understand how to change the behavior of the app based on user preferences


Debugging is the process of isolating and removing defects in software code. By understanding the debugging tools in Android Studio, Android developers can create reliable and robust applications.

To prepare for the Associate Android Developer certification exam, developers should:
Understand the basic debugging techniques available in Android Studio
Know how to debug and fix issues with an app's functional behavior and usability
Be able to use the System Log to output debug information
Understand how to use breakpoints in Android Studio
Know how to inspect variables using Android Studio


Software testing is the process of executing a program with the intent of finding errors and abnormal or unexpected behavior. Testing and test-driven development (TDD) is a critically important step of the software development process for all Android developers. It helps to reduce defect rates in commercial and enterprise software.

To prepare for the Associate Android Developer certification exam, developers should:
Thoroughly understand the fundamentals of testing
Be able to write useful local JUnit tests
Understand the Espresso UI test framework
Know how to write useful automated Android tests

Google Associate Android Developer
Google Associate learn
Killexams : Google Associate learn - BingNews Search results Killexams : Google Associate learn - BingNews Killexams : Google's learn-to-read app for kids is now available on the web

You no longer have to reach for your Android phone to try Google's learn-to-read tool. Google has launched a beta web version of Read Along that offers a similar experience on your computer. As before, the virtual helper Diya encourages your kids to read aloud and offers correctional feedback. Children can read at different skill levels and receive digital prizes for completing goals.

The beta currently supports reading on Chrome, Edge and Firefox, with functionality for Safari and other browsers due "soon." Kids can learn in several languages, including English and Hindi. You can sign in for a personalized experience, but Google makes clear that you don't need an account. All speech recognition also happens in your browser, so you don't have to worry that someone might grab your child's voice recordings.

Read Along's web version won't change your mind if you prefer the personal touch. However, Google isn't pitching this as a full substitute for human contact. It helps kids Strengthen their reading in moments where their parents aren't available, and could help schools teach literacy when one-on-one time isn't practical.

Tue, 09 Aug 2022 04:00:00 -0500 en-US text/html
Killexams : Google launches new website for kids learning to read

Filed under:

Google launches new website for kids learning to read

Kids read with Diya, a virtual assistant

A screenshot of a story in Read Along. The text reads: I have a friend. She lives in my house.
Riveting illustrated stories.

Google has released a browser version of its “Read Along” Android app. The website, while still in beta, is up and running now.

The site includes hundreds of illustrated stories at a few different reading levels. Once kids select a story, they start reading into their device’s microphone. Words are highlighted in blue after they’ve read them, and mispronounced words are underlined in red; click an underlined word, and a virtual assistant, Diya, will pronounce it for you.

A screenshot of a story in Read Along. The text reads: Three buffaloes and four birds are going to drink water.
There may be math involved in some of these stories, just as a warning.

Supported browsers include Chrome, Firefox, and Edge, while others (including Safari) are coming soon, Google says. Stories are available in English, Hindi, Gujarati, Bengali, Telugu, Marathi, Tamil, Spanish, and Portuguese.

A screenshot of Read Along showing a row of Animals stories and a row of Families stories.
Stories are grouped by Topic and level.

Google has also added new stories to Read Along’s collection, which will be available later this year in both the web and Android versions. These include adaptations of content from children’s video creators USP Studios and ChuChu TV, as well as alphabet and phonics books from education company Kutuki.

Read Along’s Android app has been used by more than 30 million kids since its launch in 2019. Not only will the move to desktop supply kids more device options, but it will also allow many to read on larger screens. This is something teachers have noted as important to young learners, especially those with visual impairments.

Tue, 09 Aug 2022 04:16:00 -0500 en text/html Killexams : Add-ons for Google Classroom are (finally) available

Starting today, add-ons for Google Classroom are available for education customers using the “teaching and learning” and “education plus” editions of Google Workspace for Education. Add-ons have been a popular component of Google Docs, Slides, Forms, and Gmail for many years and it makes sense to add these third-party integrations to a popular learning platform like Google Classroom.

For teachers, the benefit of this new classroom feature is the ability to browse and assign learning content from popular edtech tools without the hassle of setting up student accounts or sending students to an external application. For anyone who has taught elementary age students, remembering usernames and password is no small task!

Add-ons for Google Classroom is the most recent product lunch targeting education users, following practice sets for Google Classroom and the Screencast app for Chromebooks. This initial launch includes support for 18 popular edtech applications:

  • Kahoot (learning game)
  • CK-12 (curriculum)
  • Edpuzzle (video assessments)
  • Nearpod (interactive presentations
  • Peardeck (interactive presentations)
  • Google Arts & Culture (virtual museum)
  • Adobe Express (Creative tools)
  • Sora (digital library)
  • Google Play books (digital library)
  • WeVideo (video editor)
  • Formative (assessment)
  • Genially (learning activities)
  • SAFARI Montage (video lecture)
  • Wordwall (learning activities)
  • BookWidgets (learning activities)
  • PBS LearningMedia (educational video)

Additional applications are expected, however add-ons are currently in a “closed early access program” for selected partners only. Hopefully this restriction will loosen in time, paving the way for a wide array of learning applications.

Before you get too excited about using add-ons this coming school year, there are a few things you need to check. First, access to add-ons is restricted to education customers who have upgraded to either the “teaching and learning” or “education plus” edition of Google Workspace for Education.

The upgrade requirement will certainly come as a disappointment for some users, but this seems to be the trend as Google is working to make its premium offering more enticing to school districts by adding additional storage space, enhanced administrative controls, and advanced instructional tools.

Not sure which edition you are using? Here’s a Google Workspace for education feature comparison that might help!

If your school has upgraded you will still need to ask your IT administrator to approve the add-ons you are interested in using. This is a simple process that requires just a few clicks inside the Google Admin console. Google has put a lot of time and energy into this new feature. Hopefully it will be well received by teachers and students returning to the classroom this fall.

Mon, 01 Aug 2022 04:10:00 -0500 John R. Sowash en-us text/html
Killexams : What Is Google Workspace for Education?

The University of Hawai‘i was looking for something new.

More than 10 years ago, IT administrators at the sprawling public university were hosting their own email server, provisioning on-premises and running into increasing storage demands from a community of between 75,000 and 100,000 users, according to Garret Yoshimi, the university’s vice president for IT and CIO.

To ease the IT burden internally, UH decided to take what was, at the time, a somewhat unprecedented step: It became one of the first universities in the country to contract with Google and take large chunks of its operation — including email and storage — into the cloud with a service that, at the time, came to it free of charge.

Fast-forward to 2022: UH is still a Google partner, using some of the free services offered by Google Workspace for Education (formerly called G Suite for Education) and some at its now paid tier, and the university been joined by scores of higher education institutions around the world using the broad suite of tools Google offers.

Click the banner below to receive exclusive content about software in higher ed.

Along the way, the Google suite has evolved as has its relationship with higher education institutions like UH. One of those evolutions came in 2021, when Google announced it would be imposing storage limits on users for the first time, including higher education institutions. Colleges and universities now have 100 terabytes of pooled storage among their users, a number that doesn’t match demand at a place like UH. Still, after conversations with Google and internally, Yoshimi says the decision to stay with Google is a sensible one.

“We do understand that if we had to do this internally, it’s a heavy lift,” he says. “We don’t want to go back there. We were there before, a bunch of us doing our email and storage. If the number is reasonable, then it totally makes sense for us to stay with Google and not have to flip this stuff back to on-prem.”

So, what is Google Workspace for Education, what makes it a value, and what applications, storage and security features does it offer? Here’s a closer look.

READ MORE: What efficiencies can tech consolidation bring to higher ed?

What’s Included with Google Workspace for Education in Higher Ed?

Every tier of Google Workspace for Education, including the free Fundamentals tier, is made up of 15 Google applications including Gmail, Calendar, Docs, Sheets, Classroom, Jamboard, Drive, Meet and more. Additional security and analytics features are introduced at the Education Standard tier. The Teaching and Learning tier includes additional functionality like polls and breakout rooms on the Meet video platform. The premium Education Plus tier adds on more security features and learning tools.

At UH, administrators have decided to use a combination of offerings. All university users have access to the Fundamentals tier and full suite of applications. Faculty and staff, meanwhile, are signed up at the Education Plus level.

The tools all interact seamlessly and match much, if not all, of what students have been using before they reach a higher education institution, as Google platforms are the norm in K–12 schools.

Google’s tools are also, for the most part, able to integrate with other platforms, like Microsoft, which Yoshimi says is still widely used at UH.

“We’re not 100 percent Google tools by any stretch of the imagination; we do a bunch of other stuff,” he says. “One of the good things is, over time, they’ve made improvements to the product. I won’t say it’s 100 percent feature-compatible now, but it’s pretty close.”

What to Know About Google Workspace for Education’s Storage Limits

Google’s storage limit (100TB) may seem like a lot, Yoshimi says, but when he and others dug into the storage needs at the UH, it was far from sufficient. Yoshimi estimates the university is currently storing a little under 2 petabytes (2,000TB) of data.

None of us are interested in going back to the ‘we do everything on-prem’ days. It’s just not how it works anymore.”

Garret Yoshimi Vice President for IT and CIO, University of Hawai‘i

In response, Yoshimi says, UH and dozens of other institutions banded together to approach Google and discuss their concerns.

“They were really good about meeting us at the table and committing to help us figure it out,” he says. “We are continuing in conversations with Google about what happens when we need five more petabytes on the storage side, which is getting to be more and more of a requirement for large research institutions.”

Among the solutions the group has come up with, according to Yoshimi, is a runway for when the storage quotas become hard quotas and an agreement to work together with universities as they try to find alternate storage options, including purchasing cloud storage through a platform like Google Cloud.

“None of us are interested in going back to the ‘we do everything on-prem’ days. It’s just not how it works anymore,” says Yoshimi. “First, the economics don’t work, and you also tie up valuable technical resources that we have a need for in other places.”

LEARN MORE: 5 security myths about Google Workspace for Education.

Is Google Workspace for Education FERPA-Compliant and Secure?

Among the many changes Google has made to the Google Workspace for Education suite over the years, Yoshimi says, the available security features have stood out to his team with “a lot of good capabilities.” And he says his team has had no concerns about compliance with any government regulations, including the Family Educational Rights and Privacy Act, or FERPA.

“With FERPA and other acronyms that the various state and federal statutes impose on us, a big part of that is the applications that sit on top, and our policies and procedures sit on top of those,” says Yoshimi. “With the Google platform, we’re pretty comfortable in terms of compliance in those spaces.”

Security, meanwhile, has been a focus of the Google Workspace for Education suite in recent years, as cyberattacks on colleges and universities have been on the rise.

Those security features include Google Workspace for Education’s security center dashboard, available only at the paid tiers, and the ability to intercept malicious emails through the Google Security Sandbox.

fizkes/Getty Images

Wed, 03 Aug 2022 06:58:00 -0500 Andy Viano en text/html
Killexams : Researchers Partner With NIH and Google to Develop AI Learning Modules
Data science researchers will build cloud-based learning modules for biomedical research.
Photo by University Relations

Data science researchers will build cloud-based learning modules for biomedical research.

FAYETTEVILLE, Ark. – With supplemental funding from the National Institutes of Health, a team of researchers led by Justin Zhan, professor of data science at the University of Arkansas, will collaborate with NIH and Google software engineers to build cloud-based learning modules for biomedical research.

These modules will help educate biomedical researchers on the ways that artificial intelligence and machine learning, both rapidly becoming important tools in biomedical research, can enhance and streamline data analysis for different types of medical and scientific images.

The new funding, $140,135, has been awarded through the National Institute of General Medical Sciences’ Institutional Development Award Program. Zhan partnered with Kyle Quinn, associate professor of biomedical engineering, and Larry Cornett, director of the Arkansas IDeA Network of Biomedical Research Excellence at the University of Arkansas for Medical Sciences, which is administering the grant.

In addition to the Arkansas IDeA Network’s support, case studies for the learning modules will be developed with support from the data science and the imaging and spectroscopy cores of the Arkansas Integrative Metabolic Research Center.  

“Big data is transforming health and biomedical science,” Zhan said. “The new technology is rapidly expanding the quantity and variety of imaging modalities, for example, which can tell doctors so much more about their patients. But this transformation has created challenges, particularly with storing and managing massive data sets. Also, while the big data revolution transforms biology and medicine into data-driven sciences, traditional education is responding slowly. Addressing this shortcoming is part of what we’re trying to do.”

The researchers will secure the technical expertise and resources needed to provide training to students and health-care professionals on the use of artificial intelligence and machine learning, as they apply to biomedical research.

Artificial intelligence is the ability of computer systems to perform tasks that have traditionally required human intelligence. One example of artificial intelligence is machine learning, in which algorithms and computations become more accurate than humans at predicting outcomes. This process demands tremendous computational power, more than standard computer clusters can handle.  

The Arkansas researchers will parter with software engineers at Google and the National Institute of General Medical Sciences to address the computational requirements of artificial intellegence-driven research through the use of cloud computing. Cloud computing provides access to computing services over the internet, allowing faster and more flexible solutions in biomedical research.

The cloud computing modules developed by Zhan’s team will help researchers understand how artificial intelligence can be used in biomedical sciences to analyze big data. Case studies involving the identification of unique features in large biomedical image sets and the prediction of disease states is expected to help scientists, researchers and clinicians understand how to implement these powerful tools in their work.

About the Arkansas Integrative Metabolic Research Center: Established by a $10.8 million NIH grant in 2021, the Arkansas Integrative Metabolic Research Center focuses on the role of cell and tissue metabolism in disease, development, and repair through research involving advanced imaging, bioenergetics and data science. Quinn is the center director, and Zhan directs center’s Data Science Core. 

About the University of Arkansas: As Arkansas' flagship institution, the U of A provides an internationally competitive education in more than 200 academic programs. Founded in 1871, the U of A contributes more than $2.2 billion to Arkansas’ economy through the teaching of new knowledge and skills, entrepreneurship and job development, discovery through research and creative activity while also providing training for professional disciplines. The Carnegie Foundation classifies the U of A among the few U.S. colleges and universities with the highest level of research activity. U.S. News & World Report ranks the U of A among the top public universities in the nation. See how the U of A works to build a better world at Arkansas Research News.

Sun, 31 Jul 2022 17:21:00 -0500 en text/html
Killexams : Conversations to have with your child before they go to college

Soon your child will head off to college. They are fulfilling their dream — and maybe yours, too.

College is a different world from high school, even for good students. Classes will be harder, instructors' expectations different. Your child will be learning to live on their own, finding a social scene, and taking care of many details like managing a meal plan.

It takes time for most college students to figure this out, especially first-generation students.

But what if your child struggles in that first semester, before they have a chance to learn those lessons? One of five students withdraws temporarily or drops out of college after their first year; only about 60% graduate within six years, according to the National Student Clearinghouse Research Center.

Your child should know that while they will be living independently, they will not be on their own. Colleges recognize that a key part of their mission is to help students through financial, social and academic emergencies. But students need to know to ask.

With a few conversations this summer, you can supply your child a head start on learning the strategies and resources they can use to persevere.

If a college senior gets off to a bad start in a class, they know they have options. They could ask their professor or teaching assistant whether they could boost their grade with an additional assignment. They could check in with an adviser to see whether this is the right class for them. If the answer is no and there is still time, they might switch classes. Or they could reach out to the academic support center where trained professionals can help them get on track.

Many first-year students don’t know that professors welcome this sort of outreach. Such students might be intimidated to enter a support center.

Talk about how it’s OK to ask for help.

Financial stress is a major reason students drop out. Have you had a detailed conversation about budgeting yet? If not, this is the time.

Who is making sure tuition bills are paid, you or your child? What is the plan to pay those bills? What other financial support, if any, will you provide your child when they are at college? If your child calls in November to ask for $500 because they have run out of pocket money, what will you say?

Research together what resources the college provides if your child runs into a financial emergency — especially if you have limited backup funds.

Homesickness is real, and keeps some students from fully engaging in class or campus life. Ask your child if they are experiencing anxiety about attending college or living away from home. Locate resources available on campus before your child leaves home.

Resident assistants are trained to notice aberrant behavior among at-risk students and make certain they receive help to better acclimate to college life.

Make sure your child knows there is a counseling office if they need to talk. Reassure them that making an appointment isn’t a sign of weakness, it’s a sign of strength.

Save the resources you find in an easy-to-find place, like a Google document.

No matter how prepared, your child will face challenges. They need to know that there are experts on campus — professors, advisers, financial aid officers, student life officers, and counselors — dedicated to helping them meet those challenges. They just have to ask.

This guest essay reflects the views of Diann Cameron Kelly, associate provost for student success at Adelphi University.

This guest essay reflects the views of Diann Cameron Kelly, associate provost for student success at Adelphi University.

Fri, 05 Aug 2022 13:00:00 -0500 en text/html
Killexams : Google updates search result snippets for queries with quotes

Google has updated how search result snippet in Google Search for queries that contain quotes. Now, Google will show where that exact phrase appears on the page in the search result snippet in Google search, the company announced.

What this means. Google explained if you did a search such as [“google search”], the snippet will show where that exact phrase appears:

Previously. Google said previously, Google Search did not always show the quoted search phrase in the Google Search result snippet “because sometimes the quoted material appears in areas of a document that don’t lend themselves to creating helpful snippets,” Google said. “For example, a word or phrase might appear in the menu item of a page, where you’d navigate to different sections of the site. Creating a snippet around sections like that might not produce an easily readable description,” Google added.

Why the change. Google said they made this change based on searcher feedback, Google wrote “We’ve heard feedback that people doing quoted searches value seeing where the quoted material occurs on a page, rather than an overall description of the page. Our improvement is designed to help address this.”

More advice. Google then gave searchers additional advice on how quotes work in Google Search and how this may impact your search results. Check out their blog post over here.

Why we care. Google confirmed with Search Engine Land that this is not a ranking change but rather a user interface change on how Google Search will show some searches, searches that use quotes. This may impact your click-through rate from the Google search results but will have no impact on how you rank for those types of queries.

New on Search Engine Land

About The Author

Barry Schwartz a Contributing Editor to Search Engine Land and a member of the programming team for SMX events. He owns RustyBrick, a NY based web consulting firm. He also runs Search Engine Roundtable, a popular search blog on very advanced SEM topics. Barry can be followed on Twitter here.

Thu, 04 Aug 2022 04:06:00 -0500 Barry Schwartz en text/html
Killexams : Here are the skills and certifications you need to land a job in the hot AI and machine-learning markets that can pay up to $160,000

Learning platforms like Scikit-learn

Stock Photo/Getty Images

Scikit-learn helps people comprehend the basics of machine learning; and it's easy to use. Some experience in the programming language Python and a basic understanding of statistics will let users to do a lot.

There's an extensive library of standard machine-learning tools available through Scikit-learn. Companies use it for models to bucket customers into groups or predict which customers are about to leave.

There isn't a certificate for expertise in Scikit-learn because it's a fundamental part of the field. But many core machine-learning and data-science certificates like those Amazon and Microsoft offer will dig into Scikit-learn.

Statistical methodologies and SciPy

Luis Alvarez/Getty Images

Machine-learning experts need a basic understanding of statistics and probability. Modern machine-learning algorithms rely on those methodologies to help predict trends.

SciPy provides data scientists and machine-learning experts with tools for managing statistical analysis. That includes the tests they use to understand if the trends they see are significant or are flukes, a methodology called hypothesis testing.

There isn't a certificate for understanding the statistical underpinnings of machine learning, but there are courses that cover the basics on learning platforms like Udemy.

Advanced knowledge in programming languages Python or R

Python can be used for a variety of coding purposes beyond simple web development.
5432action/Getty Images

Intermediate Python knowledge can get workers far in data science, but moving on to complex machine-learning problems requires understanding more intricate parts of the programming language. 

Machine-learning experts need to know how to use Python-based packages like NumPy, a way to run algorithms on extensive datasets with many data types. For example, NumPy can help predict what a user might do with a product based on thousands of different data points.

While Python is a preferred language, many companies and institutions use another statistical-programming language, like R, instead. Most packages that work in Python also work in R.

The Python Institute offers certifications in more advanced Python skills.

Managing and visualizing large datasets with data frames like Pandas

Maskot/Getty Images

Most statistical analysis in Python will use a tool called Pandas, which lets programmers manipulate large datasets. Programmers can arrange data in columns and rows, though each entry can contain any data type.

Pandas produces graphic representations of data with visualization platforms like Matplotlib or Seaborn. That gives machine-learning experts a way to see any trends in the data and present it internally if needed.

There isn't a certification for understanding advanced Pandas usage. It's typically wrapped up in core certificate programs and data-science courses like those the learning platform DataCamp offers.

Broader machine-learning frameworks like PyTorch or TensorFlow

Sundar Pichai, the CEO of Alphabet, on stage at a product launch in 2016.
Ramin Talaie/Getty Images

Google brought AI to a more general audience in 2007 when it launched the open-source software platform TensorFlow. While TensorFlow is still ubiquitous, the open-source platform PyTorch has quickly emerged as a favorite among machine-learning experts and enthusiasts.

Machine-learning enthusiasts looking to break into AI should have a strong understanding of the strengths and weaknesses of these frameworks.

There isn't a PyTorch certification, though Facebook AI runs a free course in Udemy for PyTorch. There is also a developer certification for TensorFlow.

A deep-learning framework like Keras

Citizens learn about new AI technologies at the ARTIFICIAL Intelligence Exhibition area of the world Manufacturing Conference 2021 in Hefei, East China's Anhui Province, Nov. 19, 2021.
Xu Qingyong/Costfoto/Future Publishing via Getty Images

Machine-learning frameworks like PyTorch and TensorFlow are both highly flexible languages. But there are tools that work with the platforms to reduce the complexity and focus specifically on problems like deep learning. 

Keras is one of the most popular frameworks that sits on top of TensorFlow, opening up more complex techniques for a broader audience. Users can create deep-learning models with the framework.

Udemy hosts a course to learn both TensorFlow and Keras.

Managing immense data analysis on cloud computing

Liz Hafalia/The San Francisco Chronicle via Getty Images

Most machine-learning analysis doesn't happen on a laptop. Instead, it will occur on a cloud server, if not many of them.

Some machine-learning cloud tools like Google Colab are readily available, especially using TensorFlow. But many companies may be tied to Amazon Web Services or Microsoft Azure, and knowledge of those AI tools will be necessary to handle immense amounts of data.

Certifications like those for Amazon Web Services' machine-learning specialty cover how to handle those problems. Microsoft also offers the Azure data-science associate certification.

Thu, 14 Jul 2022 12:01:00 -0500 en-US text/html
Killexams : EPCC part of Google’s initiative to enhance digital skillset in Latinos No result found, try new keyword!El Paso Community College (EPCC) is participating in the Grow with Google HSI Career Readiness Program. The initiative will help Latino students at 35 Hispanic Serving ... Thu, 28 Jul 2022 14:46:42 -0500 en-us text/html Killexams : Google's DeepMind AI Predicts 3D Structure of Nearly Every Protein Known to Science

It wasn't until 1957 when scientists earned special access to the molecular third dimension. 

After 22 years of grueling experimentation, John Kendrew of Cambridge University finally uncovered the 3D structure of a protein. It was a twisted blueprint of myoglobin, the stringy chain of 154 amino acids that helps infuse our muscles with oxygen. As revolutionary as this discovery was, Kendrew didn't quite open up the protein architecture floodgates. During the next decade, fewer than a dozen more would be identified. 

Fast-forward to today, 65 years since that Nobel Prize-winning breakthrough. 

On Thursday, Google's sister company, DeepMind, announced it has successfully used artificial intelligence to predict the 3D structures of nearly every catalogued protein known to science. That's over 200 million proteins found in plants, bacteria, animals, humans — almost anything you can imagine.

"Essentially, you can think of it as covering the entire protein universe," Demis Hassabis, founder and CEO of DeepMind, told reporters this week.

It's thanks to AlphaFold, DeepMind's groundbreaking AI system, which has an open-source database so scientists worldwide can involve it in their research at will, and for free. Since AlphaFold's official launch in July of last year — when it had only pinpointed some 350,000 3D proteins — the program has made a noticeable dent in the landscape of research. 

"More than 500,000 researchers and biologists have used the database to view over 2 million structures," Hassabis said. "And these predictive structures have helped scientists make brilliant new discoveries."

In April, for instance, Yale University scientists called on AlphaFold's database to aid in their goal of developing a new, highly effective Malaria vaccine. And in July of last year, University of Portsmouth scientists used the system to engineer enzymes that will fight against single-use plastic pollution. 

"This moved us a year ahead of where we were, if not two," John McGeehan, director of Portsmouth's Center for Enzyme Innovation and a researcher behind the latter study, told the New York Times.

A ribbon diagram of the protein vitellogenin, featuring blue, yellow and orange ribbons.

The 3D structure of vitellogenin, which makes up egg yolk.


These endeavors are just a small trial of AlphaFold's ultimate reach.

"In the past year alone, there have been over a thousand scientific articles on a broad range of research syllabus which use AlphaFold structures; I have never seen anything like it," Sameer Velankar, DeepMind collaborator and team leader at the European Molecular Biology Laboratory's Protein Data Bank, said in a press release. 

Others who've used the database, according to Hassabis, include those trying to Strengthen our understanding of Parkinson's disease, people hoping to protect the health of honeybees and even some looking to gain valuable insight into human evolution.

"AlphaFold is already changing the way we think about the survival of molecules in the fossil record, and I can see it will soon become a fundamental tool for researchers working not only in evolutionary biology but also in archaeology and other palaeo-sciences," Beatrice Demarchi, an associate professor at the University of Turin, who recently used the system in a study on an ancient egg controversy, said in a press release.

In the coming years, DeepMind also intends to partner with teams at the Drugs For Neglected Diseases Initiative and the World Health Organization, with the goal of finding cures for little-studied, yet pervasive, tropical diseases such as Chagas disease and Leishmaniasis.

"It will make many researchers around the world think about what experiments they could do," Ewan Birney, DeepMind collaborator and deputy director of the EMBL, told reporters. "And think about what is going on in the organisms and the systems that they study."

Locks and keys

So, why do so many scientific advancements depend on this treasure chest of 3D protein modeling? Let's explain.

Suppose you're trying to make a key that fits perfectly into a lock. But you have no way of viewing the structure of that lock. All you know is this lock exists, some data about its materials, and maybe numerical information on how big each ridge is and sort of where those ridges ought to be. 

Developing this key wouldn't be impossible, maybe, but it'd be quite difficult. Keys have to be precise, otherwise they don't work. Therefore, before you get started, you'd probably try your best to model a few different mock locks with whatever info you do have so you can make your key. 

In this analogy, the lock is a protein and the key is a small molecule that binds to this protein. 

For scientists, whether they're doctors trying to craft novel medications or botanists dissecting plant anatomy to make fertilizers, interplay between certain molecules and proteins is crucial. 

With medications, for instance, the specific way a molecule in a drug binds to a protein could be the breaking point for whether it works. This interaction gets complicated because even though proteins are just strings of amino acids, they're not straight or flat. They inevitably fold, bend and sometimes tangle around themselves, like headphone wires in your pocket. 

In fact, a protein's unique folds dictate how it functions — and even the slightest of folding mistakes in the human body can lead to disease.

But returning to small molecule medications, sometimes pieces of a folded protein are blocked from binding a drug. They might happen to be folded in a strange way that makes them inaccessible, for instance. Things like this are very important bits of information for scientists trying to get their drug molecule to stick. "I think it's true that almost every drug that has come to market over the past few years has been, in part, designed through knowledge of protein structures," Janet Thornton, a research scientist at the EMBL, said in the conference. 

This is why researchers normally spend an incredible amount of time and effort to decode the folded, 3D structure of a protein they're working with in the way you'd begin your key-making journey by piecing together the lock's mould. If you know the exact structure, it becomes a lot easier to tell where and how a molecule would attach to a given protein, as well as how that attachment might affect the protein's folds in response.

But this endeavor isn't simple. Or cheap.

"The cost of solving a new, unique structure is on the order of $100,000," Steve Darnell, a structural and computational biologist from the University of Wisconsin and researcher at bioinformatics company DNAStar, said in a statement.

That's because the solution typically comes from super complicated laboratory experiments. 

Kendrew, for example, tapped into a technique called X-ray crystallography back in the day. Basically, this method requires you to take solid crystals of the protein you're interested in, place them in an X-ray beam, and watch to see what pattern the beam makes. That pattern is pretty much the position of thousands of atoms within the crystal. Only then can you use the pattern to uncover a protein's structure. 

There's also the more recent technique known as cryo-electron microscopy. This one's similar to X-ray crystallography, except the protein trial gets straight-up blasted with electrons instead of an X-ray beam. And even though it's considered much higher in resolution than the other technique, it can't exactly penetrate everything. Further, in the realm of technology, some have attempted to digitally create protein folding structures. But early tries, like a few attempts in the '80s and '90s were not great. As you can imagine, laboratory methods are also tedious — and difficult. 

Over the years, such barriers have given rise to what's called the "protein folding problem." Simply, scientists don't know how proteins fold, and have faced significant hurdles to get past that issue. 

AlphaFold's AI could be a game changer. 

Graph of the numbers of species represented in the AlphaFold database, showing 5 large circles. In each circle is a small dot representing the previous amount of proteins in the database. The larger circles are about 5 orders of magnitude larger.

A diagram provided by DeepMind of the explosive growth of the AlphaFold database, by species.


Solving the 'folding problem'

In short, AlphaFold was trained by DeepMind engineers to predict protein structures without requiring laboratory presence. No crystals, no electron firing, no $100,000 experiments.

To get AlphaFold to where it is today, first, according to the company's website, the system was exposed to 100,000 known protein folding structures. Then, as time passed, it started to learn how to decode the rest. 

It's really as straightforward as that. (Well, apart from the talent that went into coding the AI.)

"It takes, I don't know, a minimum of $20,000 and a large amount of time to crystallize a protein," Birney said. "That means experimentalists have to make choices about what they do – AlphaFold hasn't had to make choices yet." This feature of AlphaFold's thoroughness is quite fascinating. What this means is scientists have more liberty to guess and check, follow an inkling or gut instinct and cast a wide net in their research when it comes to protein structures. They won't need to worry about cost or timelines.

"The models come with a prediction error as well," Jan Kosinski, DeepMind collaborator and structural modeler at the EMBL in Hamburg, Germany said. "And usually — actually in many cases — the error is really tiny. So we call that a near-atomic precision." 

Further, the DeepMind team also says it conducted a wide variety of risk assessments to make sure using AlphaFold is safe and ethical. DeepMind team members also suggested that AI, in general, might carry biosecurity risks we hadn't thought to assess before — especially as such technology continues to permeate the medical space. 

But as the future unfolds, the DeepMind crew says AlphaFold will fluidly adapt and address such worries on a case-by-case basis. For now, it seems to be working — with a universe of protein models tracing back to a modest portrait of myoglobin.

"Only two years ago," Birney said, "we just simply did not realize that this was feasible."

Correction at 6:45 a.m. PT: Janet Thornton's last name and title have been fixed.

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