Numerous tools have been recently developed to predict disease phenotypes using single-cell RNA sequencing (RNA-seq) data. CloudPred is an end-to-end differentiable learning algorithm coupled with a biologically informed mixture model, originally tested on lupus data. This study extends CloudPred's applications to breast cancer disease phenotype prediction to test its robustness and applicability on untested and unrelated biological data. When applying a breast cancer single-cell RNA seq dataset, CloudPred achieved an area under the ROC curve (AUC) of 1 in predicting cancer status and performed better than a linear and Deepset models.
DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing
生命科学正在进入PB级测序数据的新时代。将这些大数据转换为生物学见解对计算分析来说是一个巨大的挑战。为此，我们开发了DeepMetabolism，这是一种生物学引导的深度学习系统，可以从转录组学数据中预测细胞表型。通过将无监督预训练与监督训练相结合，DeepMetabolism能够以高精度（PCC>0.92），高速度（<30 min for >使用单个GPU 100 GB数据）和高鲁棒性（容忍高达75%的噪声）预测表型。我们设想DeepMetabolism可以弥合基因型和表型之间的差距，并作为合成生物学和精准医学应用的跳板。
HPOQuest: A Rare-Disease Diagnostic Agent Using Active Phenotype Acquisition
Technical University of Munich（慕尼黑工业大学）；Helmholtz Center Munich（亥姆霍兹慕尼黑中心）；Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心）；Munich Data Science Institute (MDSI)（慕尼黑数据科学研究所）；Aalto University（阿尔托大学）
The unmasking of Mitochondrial Adam and Structural Variants larger than point mutations as stronger candidates for traits, disease phenotype and sex determination
Genomics-guided drawing of malignant regulatory signatures revealed a pivotal role of human stem cell-associated retroviral sequences (SCARS) and functionally-active hESC enhancers
Institute of Engineering in Medicine University of California, San Diego（加州大学圣地亚哥分校工程医学院）；OncoSCAR, Inc.（OncoSCAR公司）
Cancer-inspired Genomics Mapper Model for the Generation of Synthetic DNA Sequences with Desired Genomics Signatures
School of Mechanical Engineering, Tel Aviv University（特拉维夫大学机械工程学院）；Department of Cancer Biology, Cancer Institute, University College London（伦敦大学学院癌症研究所癌症生物学系）
Application of Deep Learning on Single-Cell RNA-sequencing Data Analysis: A Review
Weill Cornell Medicine（威尔康奈尔医学院）；Cornell University（康奈尔大学）；Institute for Computational Biomedicine（计算生物医学研究所）；Caryl and Israel Englander Institute for Precision Medicine（卡里尔与以色列·英格兰德精准医学研究所）；Temple University（天普大学）
Defining the relationship between cathepsin B and esophageal adenocarcinoma: conjoint analysis of Mendelian randomization, transcriptome-wide association studies, and single-cell RNA sequencing data
