Alexander Gorovits

ORCID: 0000-0002-5067-6557
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About
Contact & Profiles
Research Areas
  • Nanocluster Synthesis and Applications
  • Gold and Silver Nanoparticles Synthesis and Applications
  • Advanced biosensing and bioanalysis techniques
  • Complex Network Analysis Techniques
  • Data Visualization and Analytics
  • Genomics and Rare Diseases
  • Genetic Associations and Epidemiology
  • Human Mobility and Location-Based Analysis
  • Advanced Chemical Sensor Technologies
  • Laser Design and Applications
  • Advanced Sensor Technologies Research
  • Genetics, Bioinformatics, and Biomedical Research
  • DNA and Biological Computing
  • Laser-Matter Interactions and Applications
  • Hemophilia Treatment and Research
  • Renal Diseases and Glomerulopathies
  • Mobile Crowdsensing and Crowdsourcing
  • Opportunistic and Delay-Tolerant Networks
  • Otitis Media and Relapsing Polychondritis
  • Ocular Diseases and Behçet’s Syndrome
  • Molecular Biology Techniques and Applications
  • Fractal and DNA sequence analysis
  • Quantum Dots Synthesis And Properties
  • Cardiac electrophysiology and arrhythmias
  • RNA Research and Splicing

Regeneron (United States)
2022-2025

University at Albany, State University of New York
2018-2021

Albany Research Institute
2018

Kathie Sun Xiaodong Bai Siying Chen Suying Bao Chuanyi Zhang and 95 more Manav Kapoor Joshua Backman Tyler Joseph Evan K. Maxwell George Mitra Alexander Gorovits Adam J. Mansfield Boris Boutkov Sujit Gokhale Lukas Habegger Anthony Marcketta Adam E. Locke Liron Ganel Alicia Hawes Michael D. Kessler Deepika Sharma Jeffrey Staples Jonas Bovijn Sahar Gelfman Alessandro Di Gioia Veera M. Rajagopal Alexander Lopez Jennifer Rico Varela Jesús Alegre-Díaz Jaime Berúmen Roberto Tapia‐Conyer Pablo Kuri‐Morales Jason Torres Jonathan Emberson Rory Collins Gonçalo R. Abecasis Giovanni Coppola Andrew Deubler Aris Economides Adolfo A. Ferrando Luca A. Lotta Alan R. Shuldiner Katherine Siminovitch Christina Beechert Erin D. Brian Laura M. Cremona Hang Du Caitlin Forsythe Zhenhua Gu Kristy Guevara Michael Lattari Kia Manoochehri Prathyusha Challa Manasi Pradhan Raymond Reynoso Ricardo Schiavo Maria Sotiropoulos Padilla Chenggu Wang Sarah E. Wolf Amelia Averitt Nilanjana Banerjee Dadong Li Sameer Malhotra Justin Mower Mudasar Sarwar Jeffrey C. Staples Sean Yu Aaron Zhang Andrew Bunyea Krishna Pawan Punuru Sanjay Sreeram Gisu Eom Benjamin Sultan Rouel Lanche Vrushali Mahajan Eliot Austin Sean O’Keeffe Razvan Panea Tommy Polanco Ayesha Rasool Lance Zhang Evan Edelstein Ju Guan Olga Krasheninina Samantha Zarate Adam J. Mansfield Evan K. Maxwell Kathie Sun Manuel Allen Revez Ferreira Kathy Burch Adrián I. Campos Lei Chen Sam Choi Amy Damask Sheila M. Gaynor Benjamin Geraghty Arkopravo Ghosh Salvador Romero Martinez Christopher E. Gillies Lauren Gurski

Abstract Rare coding variants that substantially affect function provide insights into the biology of a gene 1–3 . However, ascertaining frequency such requires large sample sizes 4–8 Here we present catalogue human protein-coding variation, derived from exome sequencing 983,578 individuals across diverse populations. In total, 23% Regeneron Genetics Center Million Exome (RGC-ME) data come African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The includes more...

10.1038/s41586-024-07556-0 article EN cc-by Nature 2024-05-20
Oliver Bundgaard Vad Laia Meseguer Monfort Christian Paludan‐Müller Konstantin Kahnert Søren Zöga Diederichsen and 95 more Laura Andreasen Luca A. Lotta Jonas B. Nielsen Alicia Lundby Jesper Hastrup Svendsen Morten Olesen Aris Baras Gonçalo R. Abecasis Adolfo A. Ferrando Michael Cantor Giovanni Coppola Andrew Deubler Aris N. Economides Luca A. Lotta John D. Overton Jeffrey G. Reid Alan R. Shuldiner Katherine Siminovitch Jason Portnoy Marcus B. Jones Lyndon J. Mitnaul Alison Fenney Jonathan Marchini Manuel A. R. Ferreira Maya Ghoussaini Mona Nafde William Salerno Christina Beechert Erin D. Brian Laura M. Cremona Hang Du Caitlin Forsythe Zhenhua Gu Kristy Guevara Michael Lattari Alexander Lopez Kia Manoochehri Prathyusha Challa Manasi Pradhan Raymond Reynoso Ricardo Schiavo Maria Sotiropoulos Padilla Chenggu Wang Sarah E. Wolf Amelia Averitt Nilanjana Banerjee Dadong Li Sameer Malhotra Justin Mower Mudasar Sarwar Deepika Sharma Jeffrey Staples Sean Yu Aaron Zhang Muhammad Aqeel George Mitra Sujit Gokhale Andrew Bunyea Krishna Pawan Punuru Sanjay Sreeram Gisu Eom Benjamin Sultan Rouel Lanche Vrushali Mahajan Eliot Austin Sean O’Keeffe Razvan Panea Tommy Polanco Ayesha Rasool Xiaodong Bai Lance Zhang Boris Boutkov Evan Edelstein Alexander Gorovits Ju Guan Lukas Habegger Alicia Hawes Olga Krasheninina Samantha Zarate Adam J. Mansfield Evan K. Maxwell Suganthi Balasubramanian Suying Bao Kathie Sun Chuanyi Zhang Vikhna Raj Kumar Karuppaiya Joshua Backman Kathy Burch Adrián I. Campos Lei Chen Sam Choi Amy Damask Liron Ganel Sheila M. Gaynor Benjamin Geraghty

Atrial fibrillation (AF) has a substantial genetic component. The importance of polygenic risk is well established, while the contribution rare variants to disease warrants characterization in large cohorts.

10.1001/jamacardio.2024.1528 article EN cc-by JAMA Cardiology 2024-06-26

DNA nucleobase sequence controls the size of DNA-stabilized silver clusters, leading to their well-known yet little understood sequence-tuned colors. The enormous space possible sequences for templating clusters has challenged understanding how selects cluster properties and limited design applications that employ these clusters. We investigate genomic role fluorescent using a data-driven approach. Employing rapid parallel synthesis fluorimetry, we determine fluorescence spectra products...

10.1021/acsnano.8b03404 article EN ACS Nano 2018-07-30

ABSTRACT Coding variants that have significant impact on function can provide insights into the biology of a gene but are typically rare in population. Identifying and ascertaining frequency such requires very large sample sizes. Here, we present largest catalog human protein-coding variation to date, derived from exome sequencing 985,830 individuals diverse ancestry serve as rich resource for studying coding variants. Individuals African, Admixed American, East Asian, Middle Eastern, South...

10.1101/2023.05.09.539329 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2023-05-10

High throughput near infrared screening technology discovers DNA-stabilized silver clusters with fluorescence beyond 1000 nm.

10.1039/c8nr05781h article EN Nanoscale 2018-01-01

DNA-templated silver clusters (AgN-DNA) are known to exhibit a wide range of fluorescence colors for different choices the DNA template sequence. While these promising biosensors and biomarkers, rational design AgN-DNA is challenged by huge space possible sequences. Recent work employed machine learning methods trained on experimental data new templates that select color, specific case 10-base oligomers. An important open question whether such process developed biopolymer length applicable...

10.1021/acs.chemmater.9b04040 article EN Chemistry of Materials 2019-12-11

Communities are essential building blocks of complex networks enjoying significant research attention in terms modeling and detection algorithms. Common across models is the premise that node pairs share communities likely to interact more strongly. Moreover, most general setting a may be member multiple communities, thus, with than one cohesive group other nodes. If interactions observed over long period aggregated into single static network, hard discern due their in-network overlap....

10.1145/3219819.3220118 article EN 2018-07-19

We present an inexpensive, generalizable approach for modifying visible wavelength fluorescence microplate readers to detect emission in the near-infrared (NIR) I (650–950 nm) and NIR II (1000-1350 tissue imaging windows. These ranges are promising high sensitivity fluorescence-based cell assays biological imaging, but inaccessibility of is limiting development requisite, biocompatible fluorescent probes. Our modifications enable rapid screening candidate probes, using short pulses UV light...

10.1063/1.5023258 article EN cc-by Review of Scientific Instruments 2018-09-01

Many complex networked systems, both natural and human-made, exhibit periodic behavior driven by underlying seasonal processes: election cycles regular sporting events in social networks, cell cycle phases gene load variation infrastructure networks due to weather or daylight patterns. The "natural" periodicity may vary across network communities. At the same time this community is central (i) understating overall system dynamics (ii) for detection of communities themselves. predominant...

10.1109/icdm.2019.00092 article EN 2021 IEEE International Conference on Data Mining (ICDM) 2019-11-01

DNA-stabilized silver nanoclusters (AgN-DNAs) are a class of nanomaterials comprised 10-30 atoms held together by short synthetic DNA template strands. AgN-DNAs promising biosensors and fluorophores due to their small sizes, natural compatibility with DNA, bright fluorescence---the property absorbing light re-emitting different color. The sequence the acts as "genome" for AgN-DNAs, tuning size encapsulated nanocluster, thus its fluorescence However, current understanding AgN-DNA genome is...

10.1145/3534678.3539032 article EN Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2022-08-12

Modeling and detection of seasonality in time series is essential for accurate analysis, prediction anomaly detection. Examples seasonal effects at different scales abound: the increase consumer product sales during holiday season recurs yearly, similarly household electricity usage has daily, weekly yearly cycles. The period real-world series, however, may be obfuscated by noise missing values arising data acquisition. How can one learn natural periodicity from incomplete multivariate...

10.1109/icdm50108.2020.00183 article EN 2021 IEEE International Conference on Data Mining (ICDM) 2020-11-01
Eric Manderstedt Christina Lind‐Halldén Christer Halldén Johan Elf Peter J. Svensson and 95 more Gunnar Engström Olle Melander Aris Baras Luca A. Lotta Bengt Zöller Gonçalo R. Abecasis Adolfo A. Ferrando Aris Baras Michael Cantor Giovanni Coppola Andrew Deubler Aris N. Economides Luca A. Lotta John D. Overton Jeffrey G. Reid Alan R. Shuldiner Katherine Siminovitch John D. Overton Christina Beechert Erin D. Brian Laura M. Cremona Hang Du Caitlin Forsythe Zhenhua Gu Kristy Guevara Michael Lattari Alexander Lopez Kia Manoochehri Prathyusha Challa Manasi Pradhan Raymond Reynoso Ricardo Schiavo Maria Sotiropoulos Padilla Chenggu Wang Sarah E. Wolf Michael Cantor Amelia Averitt Nilanjana Banerjee Dadong Li Sameer Malhotra Justin Mower Mudasar Sarwar Deepika Sharma Jeffrey C. Staples Jay Sundaram Sean Yu Aaron Zhang Jeffrey G. Reid Mona Nafde George Mitra Sujit Gokhale Andrew Bunyea Janice Clauer Krishna Pawan Punuru Sanjay Sreeram Gisu Eom Sujit Gokhale Benjamin Sultan Rouel Lanche Vrushali Mahajan Eliot Austin Koteswararao Makkena Sean O’Keeffe Razvan Panea Tommy Polanco Ayesha Rasool William Salerno Xiaodong Bai Lance Zhang Boris Boutkov Evan Edelstein Alexander Gorovits Ju Guan Lukas Habegger Alicia Hawes Olga Krasheninina Samantha Zarate Adam J. Mansfield Evan K. Maxwell Suganthi Balasubramanian Suying Bao Kathie Sun Chuanyi Zhang Gonçalo R. Abecasis Manuel Allen Revez Ferreira Joshua Backman Kathy Burch Adrián I. Campos Lei Chen Sam Choi Amy Damask Liron Ganel Sheila M. Gaynor Benjamin Geraghty Akropravo Ghosh

10.1016/j.tru.2024.100190 article EN cc-by Thrombosis Update 2024-09-01

Empirical studies and theoretical models both highlight burstinessas a common temporal pattern in online behavior. A key driver for burstiness is the self-exciting nature of interactions. For example, posts groups often incite response. Such dependencies are easily lost when interaction data aggregated snapshots which subsequently analyzed independently. An alternative to model individual interactions as multi-dimensional process, thus, enforcing network dependencies. Point processes,...

10.1145/3459637.3482370 article EN 2021-10-26

While mobile devices are ubiquitous, their supporting communication infrastructure is cost-effective only in densely populated urban areas and often lacking rural settings. This lack of connectivity leads to lost opportunities applications such as emergency preparedness response. Peer-to-peer exchange that uses predictable human mobility can enable delay-tolerant information access We propose, an adaptive distributed solution for device-to-device Connectivity Optimization via REinforcement...

10.1109/secon52354.2021.9491597 article EN 2021-07-06
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