Cancers | Selected Papers in 2021–2022 in the Section “Cancer Informatics and Big Data”

We are pleased to invite you to read the 2021 and 2022 selected papers in Cancers (ISSN: 2072-6694) in the Section “Cancer Informatics and Big Data”. The paper list is as follows:

1. “The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis”
by Jacek Marzec, Helen Ross-Adams, Stefano Pirrò, Jun Wang, Yanan Zhu, Xueying Mao, Emanuela Gadaleta, Amar S. Ahmad, Bernard V. North, Solène-Florence Kammerer-Jacquet et al.
Cancers 2021, 13(2), 345; https://doi.org/10.3390/cancers13020345
Available online: https://www.mdpi.com/2072-6694/13/2/345

2. “Bioinformatic Approaches to Validation and Functional Analysis of 3D Lung Cancer Models”
by P. Jonathan Li, Jeroen P. Roose, David M. Jablons and Johannes R. Kratz
Cancers 2021, 13(4), 701; https://doi.org/10.3390/cancers13040701
Available online: https://www.mdpi.com/2072-6694/13/4/701

3. “Cancers in Agreement? Exploring the Cross-Talk of Cancer Metabolomic and Transcriptomic Landscapes Using Publicly Available Data”
by Derek van Tilborg and Edoardo Saccenti
Cancers 2021, 13(3), 393; https://doi.org/10.3390/cancers13030393
Available online: https://www.mdpi.com/2072-6694/13/3/393

4. “Comprehensively Exploring the Mutational Landscape and Patterns of Genomic Evolution in Hypermutated Cancers”
by Peng-Chan Lin, Yu-Min Yeh, Hui-Ping Hsu, Ren-Hao Chan, Bo-Wen Lin, Po-Chuan Chen, Chien-Chang Pan, Keng-Fu Hsu, Jenn-Ren Hsiao, Yan-Shen Shan et al.
Cancers 2021, 13(17), 4317; https://doi.org/10.3390/cancers13174317
Available online: https://www.mdpi.com/2072-6694/13/17/4317

5. “Epigenomic Analysis of RAD51 ChIP-seq Data Reveals cis-regulatory Elements Associated with Autophagy in Cancer Cell Lines”
by Keunsoo Kang, Yoonjung Choi, Hyeonjin Moon, Chaelin You, Minjin Seo, Geunho Kwon, Jahyun Yun, Boram Beck and Kyuho Kang
Cancers 2021, 13(11), 2547; https://doi.org/10.3390/cancers13112547
Available online: https://www.mdpi.com/2072-6694/13/11/2547

6. “Identifying Cancer Drivers Using DRIVE: A Feature-Based Machine Learning Model for a Pan-Cancer Assessment of Somatic Missense Mutations”
by Ionut Dragomir, Adnan Akbar, John W. Cassidy, Nirmesh Patel, Harry W. Clifford and Gianmarco Contino
Cancers 2021, 13(11), 2779; https://doi.org/10.3390/cancers13112779
Available online: https://www.mdpi.com/2072-6694/13/11/2779

7. “SurvCNN: A Discrete Time-to-Event Cancer Survival Estimation Framework Using Image Representations of Omics Data”
by Yogesh Kalakoti, Shashank Yadav and Durai Sundar
Cancers 2021, 13(13), 3106; https://doi.org/10.3390/cancers13133106
Available online: https://www.mdpi.com/2072-6694/13/13/3106

8. “Gene-Mutation-Based Algorithm for Prediction of Treatment Response in Colorectal Cancer Patients”
by Heather Johnson, Zahra El-Schich, Amjad Ali, Xuhui Zhang, Athanasios Simoulis, Anette Gjörloff Wingren and Jenny L. Persson
Cancers 2022, 14(8), 2045; https://doi.org/10.3390/cancers14082045
Available online: https://www.mdpi.com/2072-6694/14/8/2045

9. “Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions”
by Jens Kleesiek, Benedikt Kersjes, Kai Ueltzhöffer, Jacob M. Murray, Carsten Rother, Ullrich Köthe and Heinz-Peter Schlemmer
Cancers 2021, 13(13), 3108; https://doi.org/10.3390/cancers13133108
Available online: https://www.mdpi.com/2072-6694/13/13/3108

10. “Predicting Postoperative Complications in Cancer Patients: A Survey Bridging Classical and Machine Learning Contributions to Postsurgical Risk Analysis”
by Gonçalves, Daniel M., Rui Henriques and Rafael S. Costa
Cancers 2021, 13(13), 3217; https://doi.org/10.3390/cancers13133217
Available online: https://www.mdpi.com/2072-6694/13/13/3217

11. “Survival-Critical Genes Associated with Copy Number Alterations in Lung Adenocarcinoma”
by Chinthalapally V. Rao, Chao Xu, Mudassir Farooqui, Yuting Zhang, Adam S. Asch and Hiroshi Y. Yamada
Cancers 2021, 13(11), 2586; https://doi.org/10.3390/cancers13112586
Available online: https://www.mdpi.com/2072-6694/13/11/2586

12. “PPAR-Responsive Elements Enriched with Alu Repeats May Contribute to Distinctive PPARγ–DNMT1 Interactions in the Genome”
by Sharma Amit, Fabian Tobar-Tosse, Tikam Chand Dakal, Hongde Liu, Arijit Biswas, Athira Menon, Anoosha Paruchuri, Panagiotis Katsonis, Olivier Lichtarge, M. Michael Gromiha et al.
Cancers 2021, 13(16), 3993; https://doi.org/10.3390/cancers13163993
Available online: https://www.mdpi.com/2072-6694/13/16/3993

13. “Network-Based Analysis to Identify Drivers of Metastatic Prostate Cancer Using GoNetic”
by Louise de Schaetzen van Brienen, Giles Miclotte, Maarten Larmuseau, Jimmy Van den Eynden and Kathleen Marchal
Cancers 2021, 13(21), 5291; https://doi.org/10.3390/cancers13215291
Available online: https://www.mdpi.com/2072-6694/13/21/5291

14. “Network-Based Integration of Multi-Omics Data Identifies the Determinants of miR-491-5p Effects”
by Matthieu Meryet-Figuiere, Mégane Vernon, Mamy Andrianteranagna, Bernard Lambert, Célia Brochen, Jean-Paul Issartel, Audrey Guttin, Pascal Gauduchon, Emilie Brotin, Florent Dingli et al.
Cancers 2021, 13(16), 3970; https://doi.org/10.3390/cancers13163970
Available online: https://www.mdpi.com/2072-6694/13/16/3970

15. “Prediction of Incident Cancers in the Lifelines Population-Based Cohort”
by Francisco O. Cortés-Ibañez, Sunil Belur Nagaraj, Ludo Cornelissen, Gerjan J. Navis, Bert van der Vegt, Grigory Sidorenkov and Geertruida H. de Bock
Cancers 2021, 13(9), 2133; https://doi.org/10.3390/cancers13092133
Available online: https://www.mdpi.com/2072-6694/13/9/2133

You can check more information about the Section “Cancer Informatics and Big Data” in Cancers at the following link: https://www.mdpi.com/journal/cancers/sections/Cancer_Informatics_Big_Data.