Study Shows Machine Learning’s Potential to Predict Cancer Therapy-Related Cardiac Risk
An interdisciplinary team led by Drs. Cheng and Collier developed machine learning models that predict with promising accuracy the risk of cardiac dysfunction in cancer survivors and may be generalizable to clinical practice.
Cleveland Clinic Researchers Use “Big Data” Approach to Identify Melatonin as Possible COVID-19 Treatment
Dr. Cheng and colleagues developed a network medicine strategy to predict disease manifestations associated with COVID-19 and find existing drugs with the potential to be effective COVID-19 treatments.
Not All Mutations are Bad: Researchers Identify Differences between Benign and Pathogenic Variants
Dr. Lal’s team conducted the first big data characterization of missense variants from 1,300 disease-associated genes to identify features associated with pathogenic and benign variants.
GMI Graduate Students Win 2020 Lerner Research Institute Awards for Excellence
Sara Akhavanfard, MD, PhD, and Abigail Dooley were recognized for their outstanding scientific achievements.
GMI Fellow Wins Crile Research Fellowship Award
With this award, Takae Brewer, MD, aims to provide further insight into the genomics of breast cancer development, invasion and metastasis in the context of PTEN hamartoma tumor syndrome.
New Grant to Investigate Genomic Alterations Influencing PTEN Hamartoma Tumor Syndrome
Dr. Eng’s team will sequence the genomes of patients with PTEN hamartoma tumor syndrome to determine if and how changes in non-coding regions of the genome affect clinical outcomes.
NIH Supplement Award for COVID-19 Drug Repurposing
Dr. Cheng and his team aim to identify repurposable drugs and combination regimens to treat COVID-19 in older adults
New NIH Grant to Study Aging-Related Disorders in People with HIV
Dr. Kallianpur will investigate if kidney disease and cognitive impairment in people with HIV share an underlying mechanism and potentially highlight non-invasive biomarkers for these disorders.
NIH Awards $3.1M to Identify Novel Parkinson’s Disease Genes in Latinos
Dr. Mata and collaborators aim to pinpoint therapeutic targets for treatment and improve diagnosis and risk prediction in Latino populations.
Genetic Factors May Influence COVID-19 Susceptibility
Dr. Cheng's team found a possible association between ACE2 and TMPRSS2 polymorphisms and COVID-19 susceptibility.
WWP1 Inactivation of PTEN Drives Cancer Predisposition
A study co-led by Drs. Eng and Pandolfi identified why patients without PTEN mutations may still experience the high cancer risk associated with PTEN hamartoma tumor syndrome.
Germline Genomic Profiles of Children, Adolescents and Young Adults with Solid Tumors Inform Management and Treatment
Researchers led by Dr. Eng conducted the largest-to-date evaluation of germline mutations in children, adolescents and young adults with solid tumors and demonstrated the value of genetics evaluation and genetic testing for this patient population.
Uncovering the Link between DNA Methylation and Alternative Polyadenylation in Cancer
Dr. Ting discovered a DNA methylation-regulated alternative polyadenylation mechanism that may play an important role in cancer development.
GMI Postdoc Wins 2020 Lower Award
Dr. Lamis Yehia was named the first place winner in the clinical category.
$3.3M NIH Grant for Alzheimer’s Drug Repurposing
Dr. Cheng will develop and implement computational tools to identify and test novel repurposable drugs and drug combinations for Alzheimer’s disease.
Galaxy Closes a Data Interoperability Loop
Network-Based Drug Discovery for the Emerging COVID-19 Epidemic
By harnessing the powers of systems pharmacology and predictive modeling, Dr. Cheng identified 16 drugs and three drug combinations that may be candidates for repurposing as potential COVID-19 treatments.
Researchers Calculate Incidence Estimates for More than 100 Rare Brain Disorders
Dr. Lal adjusted and used a statistical model based on mutation rate to predict the annual number of new cases of over 100 rare monogenetic neurodevelopmental disorders caused by de novo variants, offering previously unavailable estimates for disease burden.
Harnessing AI for Drug Repurposing
A systems biology and network medicine expert, Dr. Cheng developed a deep learning methodology to more accurately predict drug-target interactions, which will help accelerate drug repurposing efforts.
Clarifying Genetic Autism Risk in PTEN Patients
In Dr. Eng’s latest study, she discovered why some patients with mutations to the PTEN gene present with cancer while others with the same mutation present with autism spectrum disorders.
2020 Caregiver Catalyst Awards Boost GMI and CPGH Research
Network-Based Tool Predicts Disease Comorbidities
GMI Postdoc Wins 2019 Cleveland Clinic Alumni Association Travel Award
GMI Postdoctoral Fellows Win Bumpus Awards at Cleveland Clinic’s Annual Research Day