Our Mission

Our Mission

Our Mission

Our Mission

Ellumigen’s mission is to make your sequencing and study data as useful and accessible as possible to your team to support with explorations and breakthrough discoveries.

We do this by creating software and AI tools that power a single workspace for true end-to-end translational-omics insight across all your studies. 
Ellumigen’s mission is to make your sequencing and study data as useful and accessible as possible to your team to support with explorations and breakthrough discoveries.

We do this by creating software and AI tools that power a single workspace for true end-to-end translational-omics insight across all your studies. 
Ellumigen’s mission is to make your sequencing and study data as useful and accessible as possible to your team to support with explorations and breakthrough discoveries.

We do this by creating software and AI tools that power a single workspace for true end-to-end translational-omics insight across all your studies. 
Ellumigen’s mission is to make your sequencing and study data as useful and accessible as possible to your team to support with explorations and breakthrough discoveries.

We do this by creating software and AI tools that power a single workspace for true end-to-end translational-omics insight across all your studies. 
Our platform includes:
Our platform includes:
Our platform includes:
Our platform includes:
Pipelines that accurately extract rich features from raw sequencing and integrate them with your study data in a high-performance structured database.
Pipelines that accurately extract rich features from raw sequencing and integrate them with your study data in a high-performance structured database
Pipelines that accurately extract rich features from raw sequencing and integrate them with your study data in a high-performance structured database.
Pipelines that accurately extract rich features from raw sequencing and integrate them with your study data in a high-performance structured database
A Chat-Based Interface that lets you explore, visualize, and interpret your data naturally — no coding or delays.
A Chat-Based Interface that lets you explore, visualize, and interpret your data naturally — no coding or delays
A Chat-Based Interface that lets you explore, visualize, and interpret your data naturally — no coding or delays.
A Chat-Based Interface that lets you explore, visualize, and interpret your data naturally — no coding or delays
Standard APIs and Notebook Access so you can apply bioinformatics tools or train custom AI models using your own workflows.
Standard APIs and Notebook Access so you can apply bioinformatics tools or train custom AI models using your own workflows.
Standard APIs and Notebook Access so you can apply bioinformatics tools or train custom AI models using your own workflows.
Standard APIs and Notebook Access so you can apply bioinformatics tools or train custom AI models using your own workflows
Fully Processed Public and Partner Datasets that provide insights beyond your own data and boost statistical power for analysis.
Fully Processed Public and Partner Datasets that provide insights beyond your own data and boost statistical power for analysis
Fully Processed Public and Partner Datasets that provide insights beyond your own data and boost statistical power for analysis.
Fully Processed Public and Partner Datasets that provide insights beyond your own data and boost statistical power for analysis
We partner with cutting-edge biopharma innovators and leading academic researchers to deliver software that drives insight, supports data-driven decisions, builds confidence in the underlying biology, and increases the probability of technical and clinical success at every step
We partner with cutting-edge biopharma innovators and leading academic researchers to deliver software that drives insight, supports data-driven decisions, builds confidence in the underlying biology, and increases the probability of technical and clinical success at every step
We partner with cutting-edge biopharma innovators and leading academic researchers to deliver software that drives insight, supports data-driven decisions, builds confidence in the underlying biology, and increases the probability of technical and clinical success at every step
We partner with cutting-edge biopharma innovators and leading academic researchers to deliver software that drives insight, supports data-driven decisions, builds confidence in the underlying biology, and increases the probability of technical and clinical success at every step

Leadership Team

Leadership Team

Leadership Team

Leadership Team

Carl Kingsford,
Ph.D.
Carl Kingsford,
Ph.D.

CEO, Co-founder

Herbert A. Simon Professor

Carnegie Mellon University

CEO, Co-founder

Herbert A. Simon Professor

Carnegie Mellon University

Eric Schultz

Eric Schultz

President, Co-founder

Center for Machine Learning and Health, Carnegie Mellon

President, Co-founder

Center for Machine Learning and Health, Carnegie Mellon

Guillaume Marçais, Ph.D.
Guillaume Marçais, Ph.D.

VP Software Development

Senior Systems Scientist

Carnegie Mellon University

VP Software Development

Senior Systems Scientist

Carnegie Mellon University

Rob Patro,
Ph.D.
Rob Patro,
Ph.D.

CTO, Co-founder

Associate Professor

University of Maryland, College Park

CTO, Co-founder

Associate Professor

University of Maryland, College Park

Gaurav Sharma,
M.S.
Gaurav Sharma,
M.S.

VP of Computational Biology and AI Strategy

VP of Computational Biology and AI Strategy

Shawn Baker

Shawn Baker

VP of AI Research and Engineering

VP of AI Research and Engineering

Thom Gulish

Office Manager

Thom Gulish

Thom Gulish

Operations Manager

Operations Manager

Carl Kingsford, Ph.D.

CEO, Co-founder

Herbert A. Simon Professor

Carnegie Mellon University

Eric Schultz

President, Co-founder

Center for Machine Learning and Health, Carnegie Mellon

Guillaume Marçais, Ph.D.

VP Software Development

Senior Systems Scientist

Carnegie Mellon University

Rob Patro, Ph.D.

CTO, Co-founder

Associate Professor

University of Maryland,

College Park

Gaurav Sharma, M.S.

VP of Computational Biology and AI Strategy

Shawn Baker

VP of AI Research and Engineering

Thom Gulish

Office Manager

Thom Gulish

Operations Manager

Carl Kingsford, Ph.D.

CEO, Co-founder

Herbert A. Simon Professor

Carnegie Mellon University

Eric Schultz

President, Co-founder

Center for Machine Learning and Health, Carnegie Mellon

Guillaume Marçais, Ph.D.

VP Software Development

Senior Systems Scientist

Carnegie Mellon University

Rob Patro, Ph.D.

CTO, Co-founder

Associate Professor

University of Maryland,

College Park

Gaurav Sharma, M.S.

VP of Computational Biology and AI Strategy

Shawn Baker

VP of AI Research and Engineering

Thom Gulish

Office Manager

Thom Gulish

Operations Manager

Advisors

Advisors

Advisors

Stan Skrzpcazk
Stan Skrzpcazk
Stan Skrzpcazk

Corporate Development


Guardent, Genomic Health

Corporate Development


Guardent, Genomic Health

Corporate Development


Guardent, Genomic Health

Michael Mentesana
Michael Mentesana
Michael Mentesana

Strategic Advisor


Syapse, PwC

Strategic Advisor


Syapse, PwC

Strategic Advisor


Syapse, PwC

Loraine Marchand
Loraine Marchand
Loraine Marchand

Strategic Advisor


Watson Health, IQVIA

Strategic Advisor


Watson Health, IQVIA

Strategic Advisor


Watson Health, IQVIA

Gertjan Bartlema
Gertjan Bartlema
Gertjan Bartlema

Strategic Advisor


Immodulon, Celgene

Strategic Advisor


Immodulon, Celgene

Strategic Advisor


Immodulon, Celgene

Christopher Williams
Christopher Williams
Christopher Williams

Strategic Advisor


MMRF, SkylineDx

Strategic Advisor


MMRF, SkylineDx

Strategic Advisor


MMRF, SkylineDx

Advisors

Stan Skrzpcazk

Corporate Development


Guardent, Genomic Health

Michael Mentesana

Strategic Advisor


Syapse, PwC

Loraine Marchand

Strategic Advisor


Watson Health, IQVIA

Gertjan Bartlema

Strategic Advisor


Immodulon, Celgene

Christopher Williams

Strategic Advisor


MMRF, SkylineDx

Scientific Advisory Board

Scientific Advisory Board

Scientific Advisory Board

Stanley Marks,
MD
Stanley Marks,
MD
Stanley Marks,
MD

Chairman, Director of Clinical Services, and Chief Medical Officer, UPMC Hillman Cancer Center

Chairman, Director of Clinical Services, and Chief Medical Officer, UPMC Hillman Cancer Center

Chairman, Director of Clinical Services, and Chief Medical Officer, UPMC Hillman Cancer Center

Edith Perez,
MD
Edith Perez,
MD
Edith Perez,
MD

Professor of Medicine, Mayo Clinic Jacksonville, FL

Professor of Medicine, Mayo Clinic Jacksonville, FL

Professor of Medicine, Mayo Clinic Jacksonville, FL

Adrian Lee,
Ph.D.
Adrian Lee,
Ph.D.
Adrian Lee,
Ph.D.

Professor and Director, Institute for Precision Medicine, University of Pittsburgh

Professor and Director, Institute for Precision Medicine, University of Pittsburgh

Professor and Director, Institute for Precision Medicine, University of Pittsburgh

David R. Gandara, MD
David R. Gandara, MD
David R. Gandara, MD

Prof. of Medicine, Thoracic Oncology (Emeritus) & Sr. Advisor, UC Davis Cancer Center

Prof. of Medicine, Thoracic Oncology (Emeritus) & Sr. Advisor, UC Davis Cancer Center

Prof. of Medicine, Thoracic Oncology (Emeritus) & Sr. Advisor, UC Davis Cancer Center

Justin Odegaard,
MD, Ph.D.
Justin Odegaard,
MD, Ph.D.
Justin Odegaard,
MD, Ph.D.

VP Clinical Development, Guardant Health

VP Clinical Development, Guardant Health

VP Clinical Development, Guardant Health

Scientific Advisory Board

Stanley Marks,
MD

Chairman, Director of Clinical Services, and Chief Medical Officer, UPMC Hillman Cancer Center

Edith Perez,
MD

Professor of Medicine, Mayo Clinic Jacksonville, FL

Adrian Lee,
Ph.D.

Professor and Director, Institute for Precision Medicine, University of Pittsburgh

David R. Gandara, MD

Prof. of Medicine, Thoracic Oncology (Emeritus) & Sr. Advisor, UC Davis Cancer Center

Justin Odegaard,
MD, Ph.D.

VP Clinical Development, Guardant Health

Our Academic Contributions

Our Academic Contributions

Our Academic Contributions

Our founding team has developed many of the most advanced and widely used software packages for sequencing analysis:
Our founding team has developed many of the most advanced and widely used software packages for sequencing analysis:
Our founding team has developed many of the most advanced and widely used software packages for sequencing analysis:

Srivastava, A. et al. Alignment and mapping methodology influence transcript abundance estimation. Genome Biol. 21, 1–29 (2020).

Srivastava, A. et al. Alignment and mapping methodology influence transcript abundance estimation. Genome Biol. 21, 1–29 (2020).

Srivastava, A. et al. Alignment and mapping methodology influence transcript abundance estimation. Genome Biol. 21, 1–29 (2020).

Ma, C. & Kingsford, C. Detecting, Categorizing, and Correcting Coverage Anomalies of RNA-Seq Quantification. Cell Syst. 9, 589-599.e7 (2019).

Ma, C. & Kingsford, C. Detecting, Categorizing, and Correcting Coverage Anomalies of RNA-Seq Quantification. Cell Syst. 9, 589-599.e7 (2019).

Ma, C. & Kingsford, C. Detecting, Categorizing, and Correcting Coverage Anomalies of RNA-Seq Quantification. Cell Syst. 9, 589-599.e7 (2019).

Ma, C., Shao, M. & Kingsford, C. SQUID: Transcriptomic structural variation detection from RNA-seq. Genome Biol. 19, 1–16 (2018).

Ma, C., Shao, M. & Kingsford, C. SQUID: Transcriptomic structural variation detection from RNA-seq. Genome Biol. 19, 1–16 (2018).

Ma, C., Shao, M. & Kingsford, C. SQUID: Transcriptomic structural variation detection from RNA-seq. Genome Biol. 19, 1–16 (2018).

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).

Shao, M. & Kingsford, C. Accurate assembly of transcripts through phase-preserving graph decomposition. Nat. Biotechnol. 35, 1167–1169 (2017).

Shao, M. & Kingsford, C. Accurate assembly of transcripts through phase-preserving graph decomposition. Nat. Biotechnol. 35, 1167–1169 (2017).

Shao, M. & Kingsford, C. Accurate assembly of transcripts through phase-preserving graph decomposition. Nat. Biotechnol. 35, 1167–1169 (2017).

Solomon, B. & Kingsford, C. Fast search of thousands of short-read sequencing experiments. Nat. Biotechnol. 34, 300–302 (2016).

Solomon, B. & Kingsford, C. Fast search of thousands of short-read sequencing experiments. Nat. Biotechnol. 34, 300–302 (2016).

Solomon, B. & Kingsford, C. Fast search of thousands of short-read sequencing experiments. Nat. Biotechnol. 34, 300–302 (2016).

Patro, R., Mount, S. M. & Kingsford, C. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat. Biotechnol. 32, 462–464 (2014).

Patro, R., Mount, S. M. & Kingsford, C. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat. Biotechnol. 32, 462–464 (2014).

Patro, R., Mount, S. M. & Kingsford, C. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat. Biotechnol. 32, 462–464 (2014).

Our Academic Contributions

Our founding team has developed many of the most advanced and widely used software packages for sequencing analysis:

Srivastava, A. et al. Alignment and mapping methodology influence transcript abundance estimation. Genome Biol. 21, 1–29 (2020).

Ma, C. & Kingsford, C. Detecting, Categorizing, and Correcting Coverage Anomalies of RNA-Seq Quantification. Cell Syst. 9, 589-599.e7 (2019).

Ma, C., Shao, M. & Kingsford, C. SQUID: Transcriptomic structural variation detection from RNA-seq. Genome Biol. 19, 1–16 (2018).

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).

Shao, M. & Kingsford, C. Accurate assembly of transcripts through phase-preserving graph decomposition. Nat. Biotechnol. 35, 1167–1169 (2017).

Solomon, B. & Kingsford, C. Fast search of thousands of short-read sequencing experiments. Nat. Biotechnol. 34, 300–302 (2016).

Patro, R., Mount, S. M. & Kingsford, C. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat. Biotechnol. 32, 462–464 (2014).

Ellumigen

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Looking to Unlock the Full Value of Your Data?

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Ellumigen

Looking to Unlock the Full Value of Your Data?

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