Ecosyste.ms: Papers
An open API service providing mapping between scientific papers and software projects that are mentioned in them.
All mentions data is based on the CZI Software Mentions dataset.
Projects: pypi: DeepTCR
https://packages.ecosyste.ms/registries/pypi.org/packages/DeepTCR
Deep Learning Methods for Parsing T-Cell Receptor Sequencing (TCRSeq) Data
136 versions
Latest release: over 2 years ago
641 downloads last month
Papers Mentioning DeepTCR 6
10.3389/fimmu.2021.680687
Immune2vec: Embedding B/T Cell Receptor Sequences in ℝN Using Natural Language ProcessingCited by: 21
Author(s): Miri Ostrovsky-Berman, Boaz Frankel, Pazit Polak, Gur Yaari
Software Mentions: 9
Published: over 3 years ago
10.7150/thno.61390
The methods and advances of adaptive immune receptors repertoire sequencingCited by: 17
Author(s): Hongmei Li, Wenjing Pan, Cheng Tang, Yujie Tang, Haijing Wu, Akihiko Yoshimura, Yan Deng, Nongyue He, Li Song
Software Mentions: 4
Published: almost 4 years ago
10.1186/s40425-018-0423-x
33rd Annual Meeting & Pre-Conference Programs of the Society for Immunotherapy of Cancer (SITC 2018)Cited by: 24
Author(s): Adi Diab, Scott S. Tykodi, Brendan D. Curti, Daniel Cho, M. K. Wong, Igor Puzanov, Karl D. Lewis, Michele Maio, Gregory A. Daniels, Alexander I. Spira, Mary Tagliaferri, Alison L. Hannah, Wendy Clemens, Michael J. Imperiale, Chantale Bernatchez, Cara L. Haymaker, Salah Eddine Bentebibel, Jonathan Zalevsky, Ute Hoch, Christie Fanton, Ahsan Rizwan, Sandra Aung, Fiore Cattaruzza, Ernesto Iaccucci, Dariusz Sawka, Mehmet Asım Bilen, Paul Lorigan, Giovanni Grignani, James Larkin, Sekwon Jang, Ewa Kalinka Warzocha, Mario Sznol, Mike Hurwitz
Software Mentions: 4
Published: about 6 years ago
10.1371/journal.pcbi.1008814
Predicting recognition between T cell receptors and epitopes with TCRGPCited by: 52
Author(s): Emmi Jokinen, Jani Huuhtanen, Satu Mustjoki, Markus Heinonen, Harri Lähdesmäki
Software Mentions: 2
Published: over 3 years ago
10.1038/s41598-021-93608-8
Deep learning identifies antigenic determinants of severe SARS-CoV-2 infection within T-cell repertoiresCited by: 8
Author(s): John-William Sidhom, Alexander S. Baras
Software Mentions: 2
Published: over 3 years ago
10.1371/journal.pcbi.1009225
Autoencoder based local T cell repertoire density can be used to classify samples and T cell receptorsCited by: 4
Author(s): Shirit Dvorkin, Reut Levi, Yoram Louzoun
Software Mentions: 1
Published: over 3 years ago