What machine learning can do for developmental biology

A scalable pipeline for designing reconfigurable organisms

(2020) Sam Kriegman et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer

(2020) Reka Hollandi et al.   Cell Systems

Cellpose: a generalist algorithm for cellular segmentation

(2020) Carsen Stringer et al.   NATURE METHODS

Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey

(2020) Longlong Jing et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Adversarial attacks on medical machine learning

(2019) Samuel G. Finlayson et al.   SCIENCE

Integrative single-cell analysis

(2019) Tim Stuart et al.   NATURE REVIEWS GENETICS

Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming

(2019) Geoffrey Schiebinger et al.   CELL

A comparison of single-cell trajectory inference methods

(2019) Wouter Saelens et al.   NATURE BIOTECHNOLOGY

Deep learning for cellular image analysis

(2019) Erick Moen et al.   NATURE METHODS

Credit data generators for data reuse

(2019) Heather H. Pierce et al.   NATURE

Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction

(2019) Chinmay Belthangady et al.   NATURE METHODS

Gene expression cartography

(2019) Mor Nitzan et al.   NATURE

ImJoy: an open-source computational platform for the deep learning era

(2019) Wei Ouyang et al.   NATURE METHODS

CLIJ: GPU-accelerated image processing for everyone

(2019) Robert Haase et al.   NATURE METHODS

Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl

(2019) Juan C. Caicedo et al.   NATURE METHODS

Comparison and Modelling of Country-level Microblog User and Activity in Cyber-physical-social Systems Using Weibo and Twitter Data

(2019) Po Yang et al.   ACM Transactions on Intelligent Systems and Technology

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images

(2018) Eric M. Christiansen et al.   CELL

Deep learning massively accelerates super-resolution localization microscopy

(2018) Wei Ouyang et al.   NATURE BIOTECHNOLOGY

Observing the cell in its native state: Imaging subcellular dynamics in multicellular organisms

(2018) Tsung-Li Liu et al.   SCIENCE

Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis

(2018) Jeffrey A. Farrell et al.   SCIENCE

The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution

(2018) James A. Briggs et al.   SCIENCE

Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo

(2018) Daniel E. Wagner et al.   SCIENCE

CellProfiler 3.0: Next-generation image processing for biology

(2018) Claire McQuin et al.   PLOS BIOLOGY

Label-free prediction of three-dimensional fluorescence images from transmitted-light microscopy

(2018) Chawin Ounkomol et al.   NATURE METHODS

In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level

(2018) Katie McDole et al.   CELL

Dimensionality reduction for visualizing single-cell data using UMAP

(2018) Etienne Becht et al.   NATURE BIOTECHNOLOGY

Content-aware image restoration: pushing the limits of fluorescence microscopy

(2018) Martin Weigert et al.   NATURE METHODS

A subcellular map of the human proteome

(2017) Peter J. Thul et al.   SCIENCE

Synthesizing developmental trajectories

(2017) Paul Villoutreix et al.   PLoS Computational Biology

The Human Cell Atlas

(2017) Aviv Regev et al.   eLife

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

Deep learning

(2015) Yann LeCun et al.   NATURE

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

(2014) Cole Trapnell et al.   NATURE BIOTECHNOLOGY

Single-cell Hi-C reveals cell-to-cell variability in chromosome structure

(2013) Takashi Nagano et al.   NATURE

viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia

(2013) El-ad David Amir et al.   NATURE BIOTECHNOLOGY

OMERO: flexible, model-driven data management for experimental biology

(2012) Chris Allan et al.   NATURE METHODS