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The Human Genetics market report Added by Market Study Report, LLC, enumerates information about the industry in terms of market share, market size, revenue forecasts, and regional outlook. The report further illustrates competitive insights of key players in the business vertical followed by an overview of their diverse portfolios and growth strategies.

The research report on Human Genetics market offers a thorough analysis of this industry vertical, while evaluating all the segments of the market. The study provides significant information concerning the key industry players and their respective gross earnings. Additionally, crucial insights regarding the geographical landscape as well as the competitive spectrum are entailed.

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Highlighting the main pointers of the Human Genetics market report:

In-depth analysis of the regional scope of Human Genetics market:

Emphasizing on the competitive spectrum of Human Genetics market:

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Other insights associated with the Human Genetics market research report:

This report considers the below mentioned key questions:

Q.1. What are some of the most favorable, high-growth prospects for the global Human Genetics market?

Q.2. Which products segments will grow at a faster rate throughout the forecast period and why?

Q.3. Which geography will grow at a faster rate and why?

Q.4. What are the major factors impacting market prospects? What are the driving factors, restraints, and challenges in this Human Genetics market?

Q.5. What are the challenges and competitive threats to the market?

Q.6. What are the evolving trends in this Human Genetics market and reasons behind their emergence?

Q.7. What are some of the changing customer demands in the Human Genetics Industry market?

Table of Contents:

Executive Summary: It includes key trends of the Human Genetics market related to products, applications, and other crucial factors. It also provides analysis of the competitive landscape and CAGR and market size of the Human Genetics market based on production and revenue.

Production and Consumption by Region: It covers all regional markets to which the research study relates. Prices and key players in addition to production and consumption in each regional market are discussed.

Key Players: Here, the report throws light on financial ratios, pricing structure, production cost, gross profit, sales volume, revenue, and gross margin of leading and prominent companies competing in the Human Genetics market.

Market Segments: This part of the report discusses about product type and application segments of the Human Genetics market based on market share, CAGR, market size, and various other factors.

Research Methodology: This section discusses about the research methodology and approach used to prepare the report. It covers data triangulation, market breakdown, market size estimation, and research design and/or programs.

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Human Genetics Market Analysis with Key Players, Applications, Trends and Forecasts to 2026 - Farmers Ledger

Scientists at Fred Hutchinson Cancer Research Center have long sought to correct the Eurocentric bias in research, particularly when it comes to cancer prevention.

We currently have a cancer risk prediction score that works in people of European descent, saidUlrike Riki Peters, PhD, MPH, a molecular and genetic epidemiologist whos been focused on this issue for more than a decade. But it doesnt predict cancer risk well in Latinx populations or Asians or African Americans or Native populations or others.

Current prevention tools like risk calculators dont work well in racially or ethnically diverse populations because theyre based primarily on the genetic data of whites about80% of the DNAsequenced by the Human Genome Project was from people of European ancestry. As a result, theyre missing the full range ofgenetic variantsthat are possible in the human genome.

Genetic research is predominantly conducted in European-descent populations that leads to a bias in the genetic risk variants that have been identified, Peters said.

And thats bad for everybody.

Without the DNA of Black and Latinx populations, Native Americans, and other racial and ethnic minorities, you cant get afullunderstanding of the human genome. You cant truly tell which genes are linked to cancer and other common diseases.

For genetics, its key to have racial and ethnic diversity, saidLi Hsu, PhD, a Hutch biostatistician. We are missing opportunities to identify important risk factors in these populations. Plus, it will teach us about biology overall and point us to new drug targets that can benefit anyone.

Now, with a $3.5 million award from the National Cancer Institute, Peters, Hsu and others are launching an ambitious effort to build more equity into cancer risk prediction. Their aim: creating and disseminating colorectal cancer risk-prediction models also known polygenic risk scores for the multiethnic populations that need them.

Eventually, these nuanced models will be used to inform screening and prevention strategies in colorectal cancers and, they hope, beyond.

Strength in Numbers

The five-year study will be conducted through theGECCO research collaboration, which Peters launched more than 10 years ago.

The Genetics and Epidemiology of Colorectal Cancer Consortium manages the genetic and epidemiological data of over 130,000 study participants from 70 studies across North America, Australia, Asia and Europe. Fred Hutch acts as GECCOs data coordinating center; Peters is the consortiums principal investigator as well as the PI of the new study, along with co-investigator Hsu.

GECCOs strength lies in its numbers. By running genome-wide association studies, or GWAS, of very large cohorts, theyve been able to identify a number of new germline, or inherited, mutations that either help or hinder the development of colorectal cancer. Theyve also accumulated extensive data on mutations that happen as a result of environmental or lifestyle exposures.

By adding up and weighing all the tiny genetic variants that can accumulate to produce a cancer, then folding in mutations or interactions that occur as a result of other exposures (think body weight, red meat consumption, alcohol and tobacco use), GECCOs researchers can create polygenic risk scores that can help pinpoint who needs to be screened early and who doesnt.

Currentguidelinesrecommend people of average risk get a colonoscopy, sigmoidoscopy or other test starting at age 50. But for three decades, colorectal cancer has been steadily increasing in peopleunder50. These early-onset cancers disproportionately affect minority populations, and both incidenceandmortality of colorectal cancer are highest in Black populations.

One option would be to lower the screening age, but that could put a huge burden on the health care system, said genetic epidemiologist Tabitha Harrison, who manages GECCOs coordinating center at the Hutch.

Youd havean additional21million peopleeligiblefor screening and that would increase health disparities since more people would be competing for limited resources, she said.

A better solution is to take the time and fix the bias now, the researchers said.

Currently, the accuracy rate of GECCOs risk-prediction model is about 64% in people under 50 and about 81% for people over 50. Thats if youre white. In nonwhites, their tool is much less effective.

The GECCO researchers believe they can do better.

Theres a lot of hype about precision medicine, about using peoples genetic risk scores to define peoples risk for disease, said Jeroen Huyghe, PhD, a statistical geneticist on the project. We cant just apply a precision model to white people. We have to apply it to all racial groups. Its important to do this now.

Harrison said using biased polygenic risk scores to inform prevention in people of color has major scientific and ethical limitations.

GWAS studies have so far been overwhelmingly Eurocentric, she said.

Personalized Cancer Prevention

For this study, the GECCO team will amass a new cohort of 121,000 colorectal cancer patients of different ethnic backgrounds from patient registries, studies and even commercial entities around the world everything from the Black Womens Health Study to the Japan Public Health Study to the Hispanic Colorectal Cancer Study to 23andMe.

By analyzing these participants existing genome-wide and epidemiological data, theyll create a risk-prediction model or risk score (or scores) for a racially and ethnically diverse population.

It would be nice to develop one score that would work across all racial and ethnic groups but we dont know if that will work, Peters said. So, well explore. Our research goal is to develop thebestrisk-prediction model. If that means we have to develop one for each racial/ethnic group, there will be multiple scores.

Once developed, these scores will help personalize the screening recommendations for various types of patients, each with different environmental exposures and inherited risks, to pinpoint those most at risk. These individuals would be tapped for an early screening, even if they dont meet the current age and family history requirements.

Theyll then use a microsimulation model developed by investigators from Erasmus University in the Netherlands to see how this screening strategy translates into clinical practice.

These types of models provide a relatively inexpensive way to estimate population-level effects including costs and benefits of policy change, Hsu said. Based on observational and experimental results and expert opinions, the model will simulate the cancer development process in a large number of individuals, from adenoma formation to colorectal cancer and mortality.

Bringing It to the Community

After validation and testing, the GECCO team will work with research partners at Moffitt Cancer Center in Florida to create a culturally appropriate, web-based risk communication tool i.e., a precision prevention app of sorts to disseminate information to patients and their health care providers.

Throughout the study, the GECCO team will work with a multiethnic community advisory board, or CAB, to ensure the results of the study as well as the new app communicate the information in a racially and ethnically sensitive way.

At each stage, we will review findings and seek guidance from our community advisory board, Peters said.

Though ambitious, Peters said the project is of great importance, especially as biased polygenic risk scores continue to be pushed out to consumers.

The limitations havent stopped a growing number of companies from commercializing European-derived polygenic risk scores, she said.

And thats a huge problem, colleagues agreed.

Using risk scores prematurely to inform colorectal cancer screening guidelines could exacerbate existing disparities in screening and survival rates, Huyghe said. Its critically important that we increase racial/ethnic diversity in genetic studies.

This article was originally published on June 18, 2020, by Hutch News. It is republished with permission.

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Building Genetic Diversity Into Cancer Research - Cancer Health Treatment News

Artificial intelligence (AI) is amplifying the pace of drug development, allowing developers to attack otherwise intractable problems and achieve results in weeks. Previously, results may have been impossible within any time frame.

As an example of the power of AI in drug development, Abraham Heifets, co-founder and CEO of Atomwise, gave the example from a commercial collaborator that was targeting a kinase as a cancer therapeutic. As a panelist at the Demy-Colton Virtual Salon Series, Drugging the Undruggable: The Power of Artificial Intelligence, he pointed out that many of the biggest companies in the pharma and biotech industries had pursued that target but all failed because of unacceptable cardiotoxicity.

AI succeeded. Approximately 99.999% of the molecules available to chemists dont exist, but are available on demand, he said.

Therefore, Atomwise ran a massive screen. It found a two-amino acid difference was all that distinguished the kinase that induced heart attacks from the one that, he said, potentially could cure cancer.

Verge Genomics uses AI to go directly to human models of disease, leapfrogging animal models. As Alice Zhang, co-founder and CEO, explained on the panel, I was frustrated at the lack of human data for ALS, Parkinsons and Alzheimers diseases. Models based on animal research dont always translate to humans. By using artificial intelligence (AI), her company is going from to a clinical trial in about two years. A small molecule amyotrophic lateral sclerosis (ALS) program is expected to enter the clinic in 2021, and four more programs are likely to join it there within two years. To achieve this, Verge built one of the largest databases of brain tissue sequences in the world, with tissue from more than 6,000 human brains.

Another company, immunai, uses AI and single cell genetics to map the immune system response. This the culmination of a perfect intersection of incredibly robust computing power, interesting AI models and mountains of data, panelist Noam Solomon, co-founder and CEO of immunai, said. Were using AI to bring intelligence. It empowers us to make better decisions.

But what exactly is AI? Originally, AI was the technology behind image and speech recognition. It allowed pattern matching on an enormous scale. Its since evolved into convolutional neural networks (CNNs), a type of artificial neural network that learns much like the human brain. It is used to analyze visual imagery, process natural language and in a variety of other applications.

Atomwise was the first to apply CNNs to molecular recognition. It uses its Artificial Intelligence Molecular Screen (AIMS) program to predict the binding characteristics of billions of molecules to a protein of interest, and narrow them to a few hundred potential targets.

We are running the largest machine learning application in the world, Heifets said. We have more than 750 projects with 600 unique targets in 40 countries. With its proprietary AI engine, AtomNet, 16 billion molecules can be screened in a matter of days.

Its important to realize, though, that for AI to deliver accurate results, users must ask the right questions in the right way.

Big data is noisy, Solomon said. So first, clean the data.

Verge eliminated much of the noise by starting its work in human, rather than animal, models. Its researchers combined its brain sequence database with human genetics and overlaid that with human-derived neurons. That combination let researchers identify gene signatures or dysregulated networks that appear in patients but not in age-mapped controls. Then they can determine which variations are causal to the condition. Looking at the convergence is the smoking gun, Solomon said, that generates greater translational success.

Although AI applications are in the public domain, these entrepreneurs developed their own, proprietary, applications. If you have an assay, for example, how important is it to know the details of how it works? Heifets asked. To identify druggable from otherwise undruggable targets, his answer was, Very.

Training the AI and validating its results are the key. Select the parameters carefully and, for training, feed the results back into the AI so it can learn. That often requires exposing it to hundreds or thousands of variations with known outcomes and then ensuring it is focusing on the correct elements of an image or a sample to make its determination.

The two greatest challenges to successfully using AI are breaking down disciplinary silos and getting AI experts (who often are from academia) to adapt to a pharmaceutical environment, the panelists agreed. They have different assumptions, such as about the ability to publish or make their algorithms open source, for example, and typically dont have backgrounds in biology, virology or related fields. Therefore, they have different disciplinary languages. Talking together regularly to solve intractable problems helps bridge those initial differences.

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Drugging the Undruggable: How AI Does the (Almost) Impossible - BioSpace

BOSTON, June 23, 2020 /PRNewswire/ -- Seven Bridges, the industry-leading bioinformatics ecosystem provider, today announced the broad availability of its graph-based methods of analysis for population genomics research addressing a longstanding concern about narrow applicability of existing genome analysis methods by using pan-genome graph references, which contain genomic variants from many populations around the world. These novel, game-changing methods will greatly improve the analysis of non-European ethnicities; support large, more diverse population studies; enable research on underrepresented populations; and aid in the development of personalized references for more precise analysis. Now available on all platforms powered by Seven Bridges, these latest graph-based methods build on the company's comprehensive offering of standard genome sequencing workflows. Seven Bridges is the first to offer a practical, scalable and accurate graph-based bioinformatics solution that effectively leverages known genomic variations of interest.

"Graph genomes have clearly emerged as the future of genetics research," said Bill Moss, CEO, Seven Bridges. "It is well known within the scientific community that the existing linear genome analysis methods do not work as well for non-European descent individuals and that they work poorly for African-descent individuals. This problem is solved by the diversity encoded in pan-genome graph references, which we employ in our latest, unprecedented offerings. I am proud that by providing the most comprehensive graph-based bioinformatics solution on the market, we are helping to drive innovative genomics research and more precise analysis for all populations."

Seven Bridges GRAF is an essential bioinformatics resource that transforms the existing linear human genome reference into a genome graph. A significant drawback to the linear reference is the inability to represent the genomic diversity of the human population, which creates a profound barrier to potentially life-saving research on non-European, understudied populations including African, Asian, Hispanic and Middle Eastern. Seven Bridges GRAF will help address the longstanding need for bioinformatics tools that can support genetics research to benefit diverse populations.

Seven Bridges GRAF enables:

Current benchmarks highlight GRAF as one of the most accurate INDEL callers in the world, able to detect even long INserted or DELeted sections in an individual's genome. INDELs contribute to much of the genomic diversity between human populations and have also been associated with many genetic disorders affecting patients around the world. However, challenges in accurately detecting INDELs, especially across diverse populations, have slowed progress in translating these findings into the clinic. GRAF removes these bottlenecks enabling researchers, geneticists and clinicians to accurately examine a more complete and representative view of an individual's genome.

Building on the strong foundation that Seven Bridges created with its initial graph genome offering, the company is now providing researchers with direct access to GRAF. Moreover, given the critical importance of making the core of scientific study more representative, Seven Bridges is providing the GRAF Germline Variant Detection Workflow and GRAF Pan Genome Referencefree of charge to academic researchers.

"Accurate detection of genetic variations for individuals from all backgrounds is essential to improving our understanding of disease and the development of targeted therapies," said Brandi Davis-Dusenbery, Chief Scientific Officer, Seven Bridges. "Even more to the point, it is critically important to the overall integrity, relevance and fundamental value of science. We feel strongly that academic researchers need easy access to these kinds of bioinformatics tools if they are to effectively advance the inclusive scope and meaningfulness of science which is why we are providing it to them at no cost."

To meet the needs of the research community, Seven Bridges will be expanding the GRAF product portfolio further with the release of additional population-specific and personalized workflows throughout 2020. Seven Bridges GRAF replaces the previous Graph Genome Suite offering. For information on GRAF, please visit sevenbridges.com/graf.

About Seven Bridges

Seven Bridges enables researchers to extract meaningful insights from genomic and phenotypic data in order to advance precision medicine. The Seven Bridges Ecosystem consists of a compliant analytic platform, intelligently curated content, transformative algorithms, unprecedented access to federated data sets, and expert on-demand professional services. This holistic approach to bioinformatics is enabling researchers at the world's leading academic, biotechnology, clinical diagnostic, government, medical centers, and pharmaceutical entities to increase R&D efficiency, enhance the hypothesis resolution process, isolate critical biomarkers, and even turn a failing clinical trial around while also reducing computational workflow times and data storage costs. To learn more, visit sevenbridges.com or follow us on LinkedIn and Twitter.

Media ContactsEric SchubertSeismic for Seven Bridges+1 415 692 6799sevenbridges@teamseismic.com

View original content to download multimedia:http://www.prnewswire.com/news-releases/seven-bridges-expands-its-pioneering-graph-based-offerings-to-advance-important-human-genome-research-301081363.html

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Seven Bridges Expands Its Pioneering Graph-Based Offerings to Advance Important Human Genome Research - P&T Community

How does coronavirus enter the body, and why does it become fatal for some compared to just a cough or fever for others? USA TODAY

As several states start to see a surge in COVID-19 cases since reopening, Ohio has not.

Ohio has gradually lifted its stay-at-home order over the past six weeks. The result: a plateau in newly reported cases and a decline in hospitalizations, both reported and estimates of people currently hospitalized. The trend in New York is alsolookinggood right now.

Florida, meanwhile, has had a noteworthy increase. Critics are saying Gov. Ron DeSantis is letting the outbreak get out of control but he is attributing the rise to more testing among low-risk individuals. He says he wont roll back reopening efforts.

CNN takes it a step further. They talked to an expert who said the state has the makings of becoming the "next large epicenter."

By the numbers:The coronavirus isn't going away anytime soon. Confirmed cases in the United States are more than 2.1 million, according to the Johns Hopkins University dashboard. America's death toll is nearing118,000. Globally, there are more than 8.4 million confirmed cases and almost450,000 people have died.

We want to hear your stories. Tell us how the pandemic has affected your life by recording a short audio clip for the Corona Diaries project.

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FYI:Employers cannot require COVID-19 antibody testing for employees returning to work, the EEOC says, but they can require other things of you. Read more from USA TODAY's Jessica Guynn.

'Smoke and mirrors':Coronavirus infections at meatpacking plants have risen from under 5,000 cases at the end of April to more than 24,000. President Donald Trump's meatpacking order has failed to keep workers safe, a USA TODAY investigation finds.

Can HIV research help find an answer? Researchers are diving deep into human genetics, hoping to find clues that might explain why many people brush off COVID-19 without even knowing they have it, while others are hospitalized or even die from the disease. Read more.

Can dogs sniff out coronavirus? Unclear, but USA TODAY's fact check team finds a claim that researchers are looking at dogs as a possible candidate to detect the disease is indeed true.

Please call for help if you need it.Thousands of anxious, stressed, isolated and uncertain callers are flooding helplines nationwide. They are teenagers and senior citizens. They have lost jobs, homes and relatives. Some express suicidal thoughts or fears that their positive COVID-19 test is a death sentence. Others reach out in the throes of a panic attack.Read more.

Want more advice on how to cope? Sign up for USA TODAY's newsletter: Staying Apart, Together.

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Contributing: Jackie Borchardt, Cincinnati Enquirer; John Kennedy and Zac Anderson, Palm Beach Post

Read or Share this story: https://www.usatoday.com/story/news/health/2020/06/18/coronavirus-news-updates-florida-up-ohio-plateaus-masks-on-planes/3212370001/

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Coronavirus news and updates: Does Florida's spike in cases make it a new 'epicenter'?; mask rules on airplanes from the FAA - USA TODAY

This study examines whether self-reported exposure to cigarette, e-cigarette, cigar, and hookah advertising, and engagement with pro-tobacco and anti-tobacco social media, are associated with past 30-day tobacco use one-year later, among young adults.Data were from two waves of the Marketing and Promotions Across Colleges in Texas study, a multi-wave study of two- and four-year Texas college students (N = 3947; M age = 23.3, SD = 2.3; 64% female; 35% white, 31% Hispanic, 19% Asian, 8% African-American/black, 7% multi-racial/other) from 24 urban-area schools. Multiple logistic regression examined longitudinal associations between recall of exposure and engagement at baseline (wave 6, spring 2017) and tobacco use at one-year follow-up (wave 7, spring 2018), accounting for baseline demographic characteristics and tobacco use.Self-reported exposure to and engagement with tobacco-related social media were significantly associated with past 30-day use of e-cigarettes, cigars, and hookah at one-year follow up; engagement was also associated with cigarette use. Controlling for other social media, exposure to any product advertising via Reddit increased risk for e-cigarette use (AOR = 1.92 [95% CI: 1.17-3.14]). Pinterest exposure increased risk for cigar use (2.92 [1.24-6.85]). Snapchat exposure increased risk for hookah use (2.94 [1.70-5.11]). Pro-tobacco engagement increased risk for future use of all products (1.77 [1.29-2.42]). Anti-tobacco engagement increased risk for use of cigars (1.59 [1.12-2.27]) and hookah (1.69 [1.27-2.25]).Findings demonstrate that encountering tobacco-related social media is an important risk factor for future tobacco use among young people. Social media should be a focus of federal regulation, counter-marketing and health communication campaigns, and intervention.Published by Elsevier B.V.

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Exposure and engagement with tobacco-related social media and associations with subsequent tobacco use among young adults: A longitudinal analysis. -...