Smita Krishnaswamy | |
---|---|
Alma mater | |
Scientific career | |
Fields | Computer Science, Genetics, Machine Learning, Electronic Design Automation |
Institutions | IBM, Yale University |
Thesis | Design, Analysis and Test of Logic Circuits under Uncertainty (2008) |
Doctoral advisor | Igor L. Markov, John P. Hayes |
Smita Krishnaswamy is an American scientist and associate professor in genetics and computer science [1] at Yale University. She specializes in the development of machine learning techniques to analyze high-dimensional high-throughput biomedical data with applications in immunology, immunotherapy, cancer, neuroscience, developmental biology and health outcomes. She organized the Open Problems in Single-Cell Biology effort with the Chan Zuckerberg Initiative and remains a scientific advisor for the project. [2]
Krishnaswamy obtained her Ph.D. in computer science and engineering from University of Michigan in 2008. [3] She then joined IBM's T.J. Watson Research Center as a scientist in the systems division, where she researched formal methods for automated error detection. Her Deltasyn algorithm was utilized in IBM System p and IBM System z high-performance server chips. [4]
Krishnaswamy switched her research efforts to biology and completed postdoctoral training in 2015 at Columbia University in the Department of Systems Biology, where she focused on learning computational models of cellular signaling from single-cell mass cytometry data. [5]
In 2022, Krishnaswamy's research, teaching and community work were honored by a FASEB Excellence in Science Award (Early-Career Investigator Award) from the Federation of American Societies for Experimental Biology funded by Eli Lilly and Company. [6]
In 2009, Krishnaswamy was the recipient of the European Design Automation Association's Outstanding Dissertation Award in the category "new directions in circuit and system test". [7]
In 2005, Krishnaswamy received a best-paper award from the Design Automation and Test in Europe conference for the paper of which she was the lead author. [8]
Krishnaswamy co-authored a book published by Springer Verlag [9] and over 50 peer-reviewed publications, including journal papers in Nature Biotechnology , [10] Nature Protocols , [11] Nature Methods [12] Science , [13] Cell [14] and conference papers in International Conference on Machine Learning. [15]
Membrane proteins are common proteins that are part of, or interact with, biological membranes. Membrane proteins fall into several broad categories depending on their location. Integral membrane proteins are a permanent part of a cell membrane and can either penetrate the membrane (transmembrane) or associate with one or the other side of a membrane. Peripheral membrane proteins are transiently associated with the cell membrane.
Systems biology is the computational and mathematical analysis and modeling of complex biological systems. It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach to biological research.
The Blue Brain Project is a Swiss brain research initiative that aims to create a digital reconstruction of the mouse brain. The project was founded in May 2005 by the Brain and Mind Institute of École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. Its mission is to use biologically-detailed digital reconstructions and simulations of the mammalian brain to identify the fundamental principles of brain structure and function.
Alice Yen-Ping Ting is Taiwanese-born American chemist. She is a professor of genetics, of biology, and by courtesy, of chemistry at Stanford University. She is also a Chan Zuckerberg Biohub investigator and a member of the National Academy of Sciences.
RNA-Seq is a sequencing technique that uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample, representing an aggregated snapshot of the cells' dynamic pool of RNAs, also known as transcriptome.
Xiaowei Zhuang is a Chinese-American biophysicist who is the David B. Arnold Jr. Professor of Science, Professor of Chemistry and Chemical Biology, and Professor of Physics at Harvard University, and an Investigator at the Howard Hughes Medical Institute. She is best known for her work in the development of Stochastic Optical Reconstruction Microscopy (STORM), a super-resolution fluorescence microscopy method, and the discoveries of novel cellular structures using STORM. She received a 2019 Breakthrough Prize in Life Sciences for developing super-resolution imaging techniques that get past the diffraction limits of traditional light microscopes, allowing scientists to visualize small structures within living cells. She was elected a Member of the American Philosophical Society in 2019 and was awarded a Vilcek Foundation Prize in Biomedical Science in 2020.
Uri Alon is a Professor and Systems Biologist at the Weizmann Institute of Science. His highly cited research investigates gene expression, network motifs and the design principles of biological networks in Escherichia coli and other organisms using both computational biology and traditional experimental wet laboratory techniques.
Aviv Regev is a computational biologist and systems biologist and Executive Vice President and Head of Genentech Research and Early Development in Genentech/Roche. She is a core member at the Broad Institute of MIT and Harvard and professor at the Department of Biology of the Massachusetts Institute of Technology. Regev is a pioneer of single cell genomics and of computational and systems biology of gene regulatory circuits. She founded and leads the Human Cell Atlas project, together with Sarah Teichmann.
Mass cytometry is a mass spectrometry technique based on inductively coupled plasma mass spectrometry and time of flight mass spectrometry used for the determination of the properties of cells (cytometry). In this approach, antibodies are conjugated with isotopically pure elements, and these antibodies are used to label cellular proteins. Cells are nebulized and sent through an argon plasma, which ionizes the metal-conjugated antibodies. The metal signals are then analyzed by a time-of-flight mass spectrometer. The approach overcomes limitations of spectral overlap in flow cytometry by utilizing discrete isotopes as a reporter system instead of traditional fluorophores which have broad emission spectra.
Dana Pe'er, Chair and Professor in Computational and Systems Biology Program at Sloan Kettering Institute is a researcher in computational systems biology. A Howard Hughes Medical Institute (HHMI) Investigator since 2021, she was previously a professor at Columbia Department of Biological Sciences. Pe'er's research focuses on understanding the organization, function and evolution of molecular networks, particularly how genetic variations alter the regulatory network and how these genetic variations can cause cancer.
Debora S. Marks is a researcher in computational biology and a Professor of Systems Biology at Harvard Medical School. Her research uses computational approaches to address a variety of biological problems.
Single-cell transcriptomics examines the gene expression level of individual cells in a given population by simultaneously measuring the RNA concentration of hundreds to thousands of genes. Single-cell transcriptomics makes it possible to unravel heterogeneous cell populations, reconstruct cellular developmental pathways, and model transcriptional dynamics — all previously masked in bulk RNA sequencing.
Single cell epigenomics is the study of epigenomics in individual cells by single cell sequencing. Since 2013, methods have been created including whole-genome single-cell bisulfite sequencing to measure DNA methylation, whole-genome ChIP-sequencing to measure histone modifications, whole-genome ATAC-seq to measure chromatin accessibility and chromosome conformation capture.
Trajectory inference or pseudotemporal ordering is a computational technique used in single-cell transcriptomics to determine the pattern of a dynamic process experienced by cells and then arrange cells based on their progression through the process. Single-cell protocols have much higher levels of noise than bulk RNA-seq, so a common step in a single-cell transcriptomics workflow is the clustering of cells into subgroups. Clustering can contend with this inherent variation by combining the signal from many cells, while allowing for the identification of cell types. However, some differences in gene expression between cells are the result of dynamic processes such as the cell cycle, cell differentiation, or response to an external stimuli. Trajectory inference seeks to characterize such differences by placing cells along a continuous path that represents the evolution of the process rather than dividing cells into discrete clusters. In some methods this is done by projecting cells onto an axis called pseudotime which represents the progression through the process.
Barbara Elizabeth Engelhardt is an American computer scientist and specialist in bioinformatics. Working as a Professor at Stanford University, her work has focused on latent variable models, exploratory data analysis for genomic data, and QTLs. In 2021, she was awarded the Overton Prize by the International Society for Computational Biology.
Sylvia Katina Plevritis is Professor and Chair of the Department of Biomedical Data Science at Stanford University.
Eileen E. M. Furlong is an Irish molecular biologist working in the fields of transcription, chromatin biology, developmental biology and genomics. She is known for her work in understanding how the genome is regulated, in particular to how developmental enhancers function, how they interact within three dimensional chromatin topologies and how they drive cell fate decisions during embryogenesis. She is Head of the Department of Genome Biology at the European Molecular Biology Laboratory (EMBL). Furlong was elected a member of the European Molecular Biology Organization (EMBO) in 2013, the Academia Europaea in 2016 and to EMBO’s research council in 2018.
Garry P. Nolan is an American immunologist, academic, inventor, and business executive. He holds the Rachford and Carlota A. Harris Professor Endowed Chair in the Department of Pathology at Stanford University School of Medicine. Nolan founded biotechnology companies, wrote numerous medical research papers, and has been active in ufology.
Single-cell genome and epigenome by transposases sequencing (scGET-seq) is a DNA sequencing method for profiling open and closed chromatin. In contrast to single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq), which only targets active euchromatin. scGET-seq is also capable of probing inactive heterochromatin.
Igor Leonidovich Markov is an American professor, computer scientist and engineer. Markov is known for mathematical and algorithmic results in quantum computation, work on limits of computation, research on algorithms for optimizing integrated circuits and on electronic design automation, as well as artificial intelligence. Additionally, Markov is a California non-profit executive responsible for aid to Ukraine worth tens of millions dollars.