Autonomous discovery in the chemical sciences part I: Progress

CW Coley, NS Eyke, KF Jensen - … Chemie International Edition, 2020‏ - Wiley Online Library
This two‐part Review examines how automation has contributed to different aspects of
discovery in the chemical sciences. In this first part, we describe a classification for …

Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review

F **ng, L Yang - IEEE reviews in biomedical engineering, 2016‏ - ieeexplore.ieee.org
Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …

TLR7/8-agonist-loaded nanoparticles promote the polarization of tumour-associated macrophages to enhance cancer immunotherapy

CB Rodell, SP Arlauckas, MF Cuccarese… - Nature biomedical …, 2018‏ - nature.com
Tumour-associated macrophages are abundant in many cancers, and often display an
immune-suppressive M2-like phenotype that fosters tumour growth and promotes resistance …

[PDF][PDF] Data-analysis strategies for image-based cell profiling

JC Caicedo, S Cooper, F Heigwer, S Warchal, P Qiu… - Nature …, 2017‏ - nature.com
Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic
differences among a variety of cell populations. It paves the way to studying biological …

A human-machine adversarial scoring framework for urban perception assessment using street-view images

Y Yao, Z Liang, Z Yuan, P Liu, Y Bie… - International Journal …, 2019‏ - Taylor & Francis
Though global-coverage urban perception datasets have been recently created using
machine learning, their efficacy in accurately assessing local urban perceptions for other …

Self-supervised deep learning encodes high-resolution features of protein subcellular localization

H Kobayashi, KC Cheveralls, MD Leonetti, LA Royer - Nature methods, 2022‏ - nature.com
Explaining the diversity and complexity of protein localization is essential to fully understand
cellular architecture. Here we present cytoself, a deep-learning approach for fully self …

A versatile active learning workflow for optimization of genetic and metabolic networks

A Pandi, C Diehl, A Yazdizadeh Kharrazi… - Nature …, 2022‏ - nature.com
Optimization of biological networks is often limited by wet lab labor and cost, and the lack of
convenient computational tools. Here, we describe METIS, a versatile active machine …

Bioengineering human myocardium on native extracellular matrix

JP Guyette, JM Charest, RW Mills, BJ Jank… - Circulation …, 2016‏ - ahajournals.org
Rationale: More than 25 million individuals have heart failure worldwide, with≈ 4000
patients currently awaiting heart transplantation in the United States. Donor organ shortage …

Reconstructing cell cycle and disease progression using deep learning

P Eulenberg, N Köhler, T Blasi, A Filby… - Nature …, 2017‏ - nature.com
We show that deep convolutional neural networks combined with nonlinear dimension
reduction enable reconstructing biological processes based on raw image data. We …

Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software

L Kamentsky, TR Jones, A Fraser, MA Bray… - …, 2011‏ - academic.oup.com
There is a strong and growing need in the biology research community for accurate,
automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered …