Welcome to MINDS!
Established in 2020, POSTECH Mathematical Institute for Data Science (MINDS) is the community of researchers in the areas of fundamental data science, machine learning, artificial intelligence, scientific computing, and humanitarian data science. MINDS mission is to provide a platform for collaboration among researchers and to provide various opportunities for students in data science. MINDS also aims to use our data science research to serve our local and global communities pursuing humanitarian data science.
News
🌟 DACON Ranker Special Lecture: Winning Strategies for AI Competitions 🌟
2023.11.30
3nd POSTECH&Peking SIAM Student Chapter Joint Conference
2023.11.01
2023 PSSC Summer Camp
2023.10.04
[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고]-상시모집
2023.07.25
[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고]
2023.07.14
[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구교수 채용 공고]
2023.06.12
Seminar | Joint seminar for probability and mathematical biology
2023.05.02
[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고]
2023.02.15
Upcoming Events
Schedule
MINDS SEMINAR
Towards realistic synthetic single-cell RNA sequencing generation with deep learning
MINDS SEMINAR
period : 2022-11-29 ~ 2022-11-29
time : 10:00:00 ~ 11:00:00
개최 장소 : Online streaming (Zoom)
Topic : Towards realistic synthetic single-cell RNA sequencing generation with deep learning
개요
Date | 2022-11-29 ~ 2022-11-29 | Time | 10:00:00 ~ 11:00:00 |
Speaker | Ali Heydari | Affiliation | UC Merced |
Place | Online streaming (Zoom) | Streaming link | ID : 688 896 1076 / PW : 54321 |
Topic | Towards realistic synthetic single-cell RNA sequencing generation with deep learning | ||
Contents | Single-cell RNA sequencing (scRNAseq) technologies allow for measurements of gene expression at a single-cell resolution. This provides researchers with a tremendous advantage for detecting heterogeneity, delineating cellular maps, or identifying rare subpopulations. However, a critical challenge in this space is the low number of single-cell observations due to limitations by rarity of subpopulation, tissue degradation, or cost. This absence of sufficient data may cause inaccuracy or irreproducibility of downstream analysis. In this talk, I will provide a brief overview of deep learning methods for generating realistic synthetic scRNAseq data, and present on ACTIVA: a novel framework for generating synthetic data using a single-stream adversarial variational autoencoder conditioned with cell-type information. Within a single framework, ACTIVA can enlarge existing datasets and generate specific subpopulations on demand, as opposed to two separate models [such as single-cell GAN (scGAN) and conditional scGAN (cscGAN)]. Data generation and augmentation with ACTIVA can enhance scRNAseq pipelines and analysis, such as benchmarking new algorithms, studying the accuracy of classifiers and detecting marker genes. ACTIVA will facilitate analysis of smaller datasets, potentially reducing the number of patients and animals necessary in initial studies. |
MinDS
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2022-11-24 14:41 ·
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POSTECH SIAM Student Chapter
🌟 DACON Ranker Special Lecture: Winning Strategies for AI Competitions 🌟
2023 POSTECH & Peking SIAM Student Chapter Joint Conference
2023 PSSC Summer Camp
2022 PSSC Summer Camp
2022 POSTECH & Peking SIAM Student Chapter Joint Conference
MINDS-MoNET-ISE Workshop
Information, Network & Topological Data Analysis
2021 POSTECH MINDS WORKSHOP
Recent Progress in Data Science and Applications
- Nov. 19(Fri) ~ Nov. 20(Sat) 2021 (1 Night 2 Days)
- Workshop homepage
Fall 2021 Seminar Series
MINDS Seminar Series on Data Science, Machine Learning, and Scientific Computing
Every Tuesdays 05:00 PM
ILJU POSTECH MINDS Workshop on TDA and ML
July 6 ~ July 9
Registration is required (please register here)