World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
43480
World Ranking
5188
National Ranking
2380

Research.com Recognitions

  • 2020 - Fellow of the American Statistical Association (ASA)
  • 2013 - Fellow of Alfred P. Sloan Foundation

Overview

Daniela Witten is affiliated with the University of Washington in the United States. Their research spans multiple fields, primarily Biochemistry, Genetics and Molecular Biology, and Mathematics.

Their work covers several subfields, including Statistics and Probability, Molecular Biology, Artificial Intelligence, Cognitive Neuroscience, and Cellular and Molecular Neuroscience.

Key topics in their research include:

  • Statistical Methods and Inference
  • Gene expression and cancer classification
  • Single-cell and spatial transcriptomics
  • Neural dynamics and brain function
  • Neuroscience and Neuropharmacology Research
  • Bioinformatics and Genomic Networks
  • Advanced Statistical Methods and Models

Recent publications authored or coauthored by Daniela Witten demonstrate a focus on statistical methodologies and applications in biology and medicine. Notable papers include:

  • "Selective Inference for Hierarchical Clustering" (2022), Journal of the American Statistical Association
  • "Inference after latent variable estimation for single-cell RNA sequencing data" (2022), Biostatistics
  • "Testing for a Change in Mean after Changepoint Detection" (2022), Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • "Modeling microbial abundances and dysbiosis with beta-binomial regression" (2020), The Annals of Applied Statistics
  • "Machine learning techniques for mitoses classification" (2020), Computerized Medical Imaging and Graphics

Daniela Witten frequently collaborates with several researchers, including Gareth James, Trevor Hastie, Robert Tibshirani, Anna Neufeld, and Lucy L. Gao, each with numerous joint publications.

Their work has appeared in well-known publication venues such as:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of the American Statistical Association
  • Biostatistics
  • Computerized Medical Imaging and Graphics

Daniela Witten has contributed to books published by Springer International Publishing, including two editions of "An Introduction to Statistical Learning" released in 2021 and 2023.

Their contributions to statistical science have been recognized through fellowships, including being named a Fellow of the American Statistical Association in 2020 and a Fellow of the Alfred P. Sloan Foundation in 2013.

Best Publications

  • An introduction to statistical learning

    Gareth James;Daniela Witten;Trevor Hastie;Robert Tibshirani

  • A general framework for estimating the relative pathogenicity of human genetic variants

    Martin Kircher;Daniela M Witten;Preti Jain;Brian J O'Roak;Brian J O'Roak

  • CADD: predicting the deleteriousness of variants throughout the human genome.

    Philipp Rentzsch;Daniela M. Witten;Gregory M. Cooper;Jay Shendure

  • An Introduction to Statistical Learning: with Applications in R

    Gareth James;Daniela Witten;Trevor Hastie;Robert Tibshirani

  • The joint graphical lasso for inverse covariance estimation across multiple classes

    Patrick Danaher;Pei Wang;Daniela M. Witten

  • A framework for feature selection in clustering

    Daniela M. Witten;Robert Tibshirani

  • Sparse Discriminant Analysis

    Line Katrine Harder Clemmensen;Trevor Hastie;Daniela Witten;Bjarne Kjær Ersbøll

  • Extensions of sparse canonical correlation analysis with applications to genomic data.

    Daniela M Witten;Robert J. Tibshirani

  • Massively parallel functional dissection of mammalian enhancers in vivo

    Rupali P. Patwardhan;Joseph B. Hiatt;Daniela M. Witten;Mee J. Kim

  • Penalized classification using Fisher's linear discriminant

    Daniela M. Witten;Robert Tibshirani

  • Normalization, testing, and false discovery rate estimation for RNA-sequencing data

    Jun Li;Daniela M. Witten;Iain M. Johnstone;Robert Tibshirani

  • New Insights and Faster Computations for the Graphical Lasso

    Daniela M. Witten;Jerome H. Friedman;Noah Simon

  • The Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT): A New Tool for the Psychosocial Evaluation of Pre-Transplant Candidates

    José R. Maldonado;Holly C. Dubois;Evonne E. David;Yelizaveta Sher

  • A systematic comparison reveals substantial differences in chromosomal versus episomal encoding of enhancer activity

    Fumitaka Inoue;Martin Kircher;Beth Martin;Gregory M. Cooper

  • A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex

    Saskia E. J. de Vries;Jerome A. Lecoq;Michael A. Buice;Peter A. Groblewski

  • Covariance-regularized regression and classification for high-dimensional problems

    Daniela M. Witten;Robert Tibshirani

  • Classification and clustering of sequencing data using a Poisson model

    Daniela M. Witten

  • Transcriptional profiling of long non-coding RNAs and novel transcribed regions across a diverse panel of archived human cancers.

    Alayne L Brunner;Andrew H Beck;Andrew H Beck;Badreddin Edris;Robert T Sweeney

  • A comparative study of machine learning methods for authorship attribution

    Matthew L. Jockers;Daniela M. Witten

  • A general framework for estimating the relative pathogenicity of human genetic variants

    Martin Kircher;Daniela M. Witten;Gregory M. Cooper;Jay Shendure

  • Sparse canonical correlation analysis, with applications to genomic data

    Daniela M. Witten;Robert Tibshirani

Frequent Co-Authors

Robert Tibshirani
Robert Tibshirani Stanford University
Trevor Hastie
Trevor Hastie Stanford University
Jay Shendure
Jay Shendure University of Washington
Gregory M. Cooper
Gregory M. Cooper HudsonAlpha Institute for Biotechnology
Martin Kircher
Martin Kircher Charité - University Medicine Berlin
Aarno Palotie
Aarno Palotie University of Helsinki
Markus Perola
Markus Perola Finnish Institute for Health and Welfare
Mark J. Daly
Mark J. Daly Massachusetts General Hospital
Benjamin M. Neale
Benjamin M. Neale Harvard University
Eric Boerwinkle
Eric Boerwinkle The University of Texas Health Science Center at Houston

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