| iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning K Rychel, K Decker, AV Sastry, PV Phaneuf, S Poudel, BO Palsson Nucleic acids research 49 (D1), D112-D120, 2021 | 85 | 2021 |
| Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome K Rychel, AV Sastry, BO Palsson Nature communications 11 (1), 6338, 2020 | 62 | 2020 |
| A multi-scale expression and regulation knowledge base for Escherichia coli CR Lamoureux, KT Decker, AV Sastry, K Rychel, Y Gao, JL McConn, ... Nucleic Acids Research 51 (19), 10176-10193, 2023 | 35 | 2023 |
| Mining all publicly available expression data to compute dynamic microbial transcriptional regulatory networks AV Sastry, S Poudel, K Rychel, R Yoo, CR Lamoureux, S Chauhan, ... BioRxiv, 2021.07. 01.450581, 2021 | 34 | 2021 |
| Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network HG Lim, K Rychel, AV Sastry, GJ Bentley, J Mueller, HS Schindel, ... Metabolic Engineering 72, 297-310, 2022 | 33 | 2022 |
| Microporous polymer scaffolds for the transplantation of embryonic stem cell derived pancreatic progenitors to a clinically translatable site for the treatment of type I diabetes T Kasputis, D Clough, F Noto, K Rychel, B Dye, LD Shea ACS biomaterials science & engineering 4 (5), 1770-1778, 2018 | 33 | 2018 |
| Machine learning of all Mycobacterium tuberculosis H37Rv RNA-seq data reveals a structured interplay between metabolism, stress response, and infection R Yoo, K Rychel, S Poudel, T Al-Bulushi, Y Yuan, S Chauhan, ... MSphere 7 (2), e00033-22, 2022 | 30 | 2022 |
| Machine learning from Pseudomonas aeruginosa transcriptomes identifies independently modulated sets of genes associated with known transcriptional regulators A Rajput, H Tsunemoto, AV Sastry, R Szubin, K Rychel, J Sugie, ... Nucleic acids research 50 (7), 3658-3672, 2022 | 30 | 2022 |
| Emerging themes and unifying concepts underlying cell behavior regulation by the pericellular space KE Scott, K Rychel, S Ranamukhaarachchi, P Rangamani, SI Fraley Acta biomaterialia 96, 81-98, 2019 | 24 | 2019 |
| Machine Learning Uncovers a Data-Driven Transcriptional Regulatory Network for the Crenarchaeal Thermoacidophile Sulfolobus acidocaldarius SM Chauhan, S Poudel, K Rychel, C Lamoureux, R Yoo, T Al Bulushi, ... Frontiers in Microbiology 12, 753521, 2021 | 23 | 2021 |
| Advanced transcriptomic analysis reveals the role of efflux pumps and media composition in antibiotic responses of Pseudomonas aeruginosa A Rajput, H Tsunemoto, AV Sastry, R Szubin, K Rychel, SM Chauhan, ... Nucleic acids research 50 (17), 9675-9688, 2022 | 19 | 2022 |
| Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance K Rychel, J Tan, A Patel, C Lamoureux, Y Hefner, R Szubin, J Johnsen, ... Cell reports 42 (9), 2023 | 16* | 2023 |
| Pan-genome analysis of transcriptional regulation in six Salmonella enterica serovar typhimurium strains reveals their different regulatory structures Y Yuan, Y Seif, K Rychel, R Yoo, S Chauhan, S Poudel, T Al-Bulushi, ... Msystems 7 (6), e00467-22, 2022 | 14* | 2022 |
| Systems biology of competency in Vibrio natriegens is revealed by applying novel data analytics to the transcriptome J Shin, K Rychel, BO Palsson Cell Reports 42 (6), 2023 | 12 | 2023 |
| Elucidation of independently modulated genes in Streptococcus pyogenes reveals carbon sources that control its expression of hemolytic toxins Y Hirose, S Poudel, AV Sastry, K Rychel, CR Lamoureux, R Szubin, ... Msystems 8 (3), e00247-23, 2023 | 8 | 2023 |
| proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms KT Decker, Y Gao, K Rychel, T Al Bulushi, SM Chauhan, D Kim, BK Cho, ... Nucleic acids research 50 (D1), D1077-D1084, 2022 | 8 | 2022 |
| Predicting stress response and improved protein overproduction in Bacillus subtilis JD Tibocha-Bonilla, C Zuñiga, A Lekbua, C Lloyd, K Rychel, K Short, ... NPJ Systems Biology and Applications 8 (1), 50, 2022 | 7 | 2022 |
| Machine learning of all Mycobacterium tuberculosis H37Rv RNA-seq data reveals a structured interplay between metabolism, stress response, and infection. MSphere. 2022; 7 (2 … R Yoo, K Rychel, S Poudel, T Al-Bulushi, Y Yuan, S Chauhan DOI 10, 00033-22, 0 | 7 | |
| The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions C Dalldorf, K Rychel, R Szubin, Y Hefner, A Patel, DC Zielinski, ... Msystems, e00305-24, 2024 | 6 | 2024 |
| Proteome allocation is linked to transcriptional regulation through a modularized transcriptome A Patel, D McGrosso, Y Hefner, A Campeau, AV Sastry, S Maurya, ... Nature Communications 15 (1), 5234, 2024 | 5 | 2024 |
