Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data

Autor: Jovan, Tanevski, Thin, Nguyen, Buu, Truong, Nikos, Karaiskos, Mehmet Eren Ahsen, Xinyu, Zhang, Chang, Shu, Ke, Xu, Xiaoyu, Liang, Ying, Hu, Hoang VV Pham, Xiaomei, Li, Thuc, D Le, Adi, L Tarca, Gaurav, Bhatti, Roberto, Romero, Nestoras, Karathanasis, Phillipe, Loher, Yang, Chen, Zhengqing, Ouyang, Disheng, Mao, Yuping, Zhang, Maryam, Zand, Jianhua, Ruan, Christoph, Hafemeister, Peng, Qiu, Duc, Tran, Tin, Nguyen, Attila, Gabor, Thomas, Yu, Justin, Guinney, Enrico, Glaab, Roland, Krause, Peter, Banda, DREAM SCTC Consortium, Baruzzo, Giacomo, Cappellato, Marco, Zorzan, Irene, DEL FAVERO, Simone, Schenato, Luca, Vandin, Fabio, DI CAMILLO, Barbara, Shruti, Gupta, Ajay Kumar Verma, Shandar, Ahmad, Ronesh, Sharma, Edwin, Vans, Alok, Sharma, Ashwini, Patil, Alejandra, Carrea, Alonso, Andres M., Luis, Diambra, Vijay, Narsapuram, Vinay, Kaikala, Chaitanyam, Potnuru, Sunil, Kumar, Jiajie, Peng, Xiaoyu, Wang, Xuequn, Shang, Dani, Livne, Tom, Snir, Hagit, Philip, Alona, Zilberberg, Sol, Efroni, Hamid Reza Hassanzadeh, Reihaneh, Hassanzadeh, Ghazal, Jahanshahi, M-Mahdi, Naddaf-Sh, Drayer, Phillip M., Sadra, Naddaf-Sh, Marouen Ben Guebila, Changlin, Wan, Yuchen, Cao, Saber, Meamardoost, Nan Papili Gao, Rudiyanto, Gunawan, Gustavo, Stolovitzky, Nikolaus, Rajewsky, Julio, Saez-Rodriguez, Pablo, Meyer

Publikováno v: Life Science Alliance

We describe and provide an array of diverse methods to predict cellular positions in tissue from RNA-seq data selecting mapping genes according to their spatial/statistical properties and their effect on improving the cell positioning.
Single-ce

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24f19c28fbdbe4c77371a58fd92e3a3b
http://edoc.mdc-berlin.de/19409/1/19409oa.pdf

FEATS: feature selection-based clustering of single-cell RNA-seq data

Autor: Ashwini Patil, Edwin Vans, Alok Sharma

Publikováno v: Briefings in bioinformatics. 22(4)

Motivation Advances in next-generation sequencing have made it possible to carry out transcriptomic studies at single-cell resolution and generate vast amounts of single-cell RNA sequencing (RNA-seq) data rapidly. Thus, tools to analyze this data nee

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ef010da5e93fd2171f48f5d61047990
https://pubmed.ncbi.nlm.nih.gov/33285568

Clustering of Small-Sample Single-Cell RNA-Seq Data via Feature Clustering and Selection

Autor: Edwin Vans, Tatsuhiko Tsunoda, Alokanand Sharma, Daichi Shigemizu, Ashwini Patil

Publikováno v: PRICAI 2019: Trends in Artificial Intelligence ISBN: 9783030298937
PRICAI (3)

We present FeatClust, a software tool for clustering small sample size single-cell RNA-Seq datasets. The FeatClust approach is based on feature selection. It divides features into several groups by performing agglomerative hierarchical clustering and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3cb5ca1587fbb69870a48d51a6829f47
https://doi.org/10.1007/978-3-030-29894-4_36

Vision Based Autonomous Path Tracking of a Mobile Robot using Fuzzy Logic

Autor: Edwin Vans, Alok Sharma, Gancho Vachkov

In this paper we present an algorithm for autonomous path tracking of a mobile robot to track straight and curved paths traced in the environment. The algorithm uses a fuzzy logic based approach for path tracking so that human driving behavior can be

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8bde17a8c990b75c78580a3aa0bc215