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Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling.

Journal of molecular biology

Cui H, Zhao N, Korkin D.
PMID: 30017919
J Mol Biol. 2018 Sep 14;430(18):2974-2992. doi: 10.1016/j.jmb.2018.07.012. Epub 2018 Jul 12.

Non-synonymous mutations linked to the complex diseases often have a global impact on a biological system, affecting large biomolecular networks and pathways. However, the magnitude of the mutation-driven effects on the macromolecular network is yet to be fully explored....

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Cui H, Zhao N, Korkin D. Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling. J Mol Biol. 2018;430(18):2974-2992doi: 10.1016/j.jmb.2018.07.012.
Cui, H., Zhao, N., & Korkin, D. (2018). Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling. Journal of molecular biology, 430(18), 2974-2992. https://doi.org/10.1016/j.jmb.2018.07.012
Cui, Hongzhu, et al. "Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling." Journal of molecular biology vol. 430,18 (2018): 2974-2992. doi: https://doi.org/10.1016/j.jmb.2018.07.012
Cui H, Zhao N, Korkin D. Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling. J Mol Biol. 2018 Sep 14;430(18):2974-2992. doi: 10.1016/j.jmb.2018.07.012. Epub 2018 Jul 12. PMID: 30017919.
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The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease.

American journal of respiratory cell and molecular biology

Schiller HB, Montoro DT, Simon LM, Rawlins EL, Meyer KB, Strunz M, Vieira Braga FA, Timens W, Koppelman GH, Budinger GRS, Burgess JK, Waghray A, van den Berge M, Theis FJ, Regev A, Kaminski N, Rajagopal J, Teichmann SA, Misharin AV, Nawijn MC.
PMID: 30995076
Am J Respir Cell Mol Biol. 2019 Jul;61(1):31-41. doi: 10.1165/rcmb.2018-0416TR.

Lung disease accounts for every sixth death globally. Profiling the molecular state of all lung cell types in health and disease is currently revolutionizing the identification of disease mechanisms and will aid the design of novel diagnostic and personalized...

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Schiller HB, Montoro DT, Simon LM, et al. The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease. Am J Respir Cell Mol Biol. 2019;61(1):31-41doi: 10.1165/rcmb.2018-0416TR.
Schiller, H. B., Montoro, D. T., Simon, L. M., Rawlins, E. L., Meyer, K. B., Strunz, M., Vieira Braga, F. A., Timens, W., Koppelman, G. H., Budinger, G. R. S., Burgess, J. K., Waghray, A., van den Berge, M., Theis, F. J., Regev, A., Kaminski, N., Rajagopal, J., Teichmann, S. A., Misharin, A. V., & Nawijn, M. C. (2019). The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease. American journal of respiratory cell and molecular biology, 61(1), 31-41. https://doi.org/10.1165/rcmb.2018-0416TR
Schiller, Herbert B, et al. "The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease." American journal of respiratory cell and molecular biology vol. 61,1 (2019): 31-41. doi: https://doi.org/10.1165/rcmb.2018-0416TR
Schiller HB, Montoro DT, Simon LM, Rawlins EL, Meyer KB, Strunz M, Vieira Braga FA, Timens W, Koppelman GH, Budinger GRS, Burgess JK, Waghray A, van den Berge M, Theis FJ, Regev A, Kaminski N, Rajagopal J, Teichmann SA, Misharin AV, Nawijn MC. The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease. Am J Respir Cell Mol Biol. 2019 Jul;61(1):31-41. doi: 10.1165/rcmb.2018-0416TR. PMID: 30995076; PMCID: PMC6604220.
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Reply.

Gastroenterology

Wada Y, Zhu Z, Goel A.
PMID: 34529991
Gastroenterology. 2022 Jan;162(1):348-349. doi: 10.1053/j.gastro.2021.09.013. Epub 2021 Sep 14.

No abstract available.

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Wada Y, Zhu Z, Goel A. Reply. Gastroenterology. 2021;162(1):348-349doi: 10.1053/j.gastro.2021.09.013.
Wada, Y., Zhu, Z., & Goel, A. (2022). Reply. Gastroenterology, 162(1), 348-349. https://doi.org/10.1053/j.gastro.2021.09.013
Wada, Yuma, et al. "Reply." Gastroenterology vol. 162,1 (2022): 348-349. doi: https://doi.org/10.1053/j.gastro.2021.09.013
Wada Y, Zhu Z, Goel A. Reply. Gastroenterology. 2022 Jan;162(1):348-349. doi: 10.1053/j.gastro.2021.09.013. Epub 2021 Sep 14. PMID: 34529991.
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Transcriptome-wide Association Study in Frontotemporal Dementia Identifies New Disease Loci by In Silico Analysis.

Biological psychiatry

Lill CM.
PMID: 33766241
Biol Psychiatry. 2021 Apr 15;89(8):e37-e39. doi: 10.1016/j.biopsych.2021.02.010.

No abstract available.

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Lill CM. Transcriptome-wide Association Study in Frontotemporal Dementia Identifies New Disease Loci by In Silico Analysis. Biol Psychiatry. 2021;89(8):e37-e39doi: 10.1016/j.biopsych.2021.02.010.
Lill, C. M. (2021). Transcriptome-wide Association Study in Frontotemporal Dementia Identifies New Disease Loci by In Silico Analysis. Biological psychiatry, 89(8), e37-e39. https://doi.org/10.1016/j.biopsych.2021.02.010
Lill, Christina M. "Transcriptome-wide Association Study in Frontotemporal Dementia Identifies New Disease Loci by In Silico Analysis." Biological psychiatry vol. 89,8 (2021): e37-e39. doi: https://doi.org/10.1016/j.biopsych.2021.02.010
Lill CM. Transcriptome-wide Association Study in Frontotemporal Dementia Identifies New Disease Loci by In Silico Analysis. Biol Psychiatry. 2021 Apr 15;89(8):e37-e39. doi: 10.1016/j.biopsych.2021.02.010. PMID: 33766241.
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CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression.

IEEE/ACM transactions on computational biology and bioinformatics

Mu Q, Wang J.
PMID: 31581092
IEEE/ACM Trans Comput Biol Bioinform. 2021 Jan-Feb;18(1):306-311. doi: 10.1109/TCBB.2019.2944827. Epub 2021 Feb 03.

Detection of DNA copy number alteration in cancer cells is critical to understanding cancer initiation and progression. Widely used methods, such as DNA arrays and genomic DNA sequencing, are relatively expensive and require DNA samples at a microgram level,...

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Mu Q, Wang J. CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression. IEEE/ACM Trans Comput Biol Bioinform. 2021;18(1):306-311doi: 10.1109/TCBB.2019.2944827.
Mu, Q., & Wang, J. (2021). CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression. IEEE/ACM transactions on computational biology and bioinformatics, 18(1), 306-311. https://doi.org/10.1109/TCBB.2019.2944827
Mu, Quanhua, and Wang, Jiguang. "CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression." IEEE/ACM transactions on computational biology and bioinformatics vol. 18,1 (2021): 306-311. doi: https://doi.org/10.1109/TCBB.2019.2944827
Mu Q, Wang J. CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression. IEEE/ACM Trans Comput Biol Bioinform. 2021 Jan-Feb;18(1):306-311. doi: 10.1109/TCBB.2019.2944827. Epub 2021 Feb 03. PMID: 31581092.
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Transcriptome skimming of lentil (Lens culinaris Medikus) cultivars with contrast reaction to salt stress.

Functional & integrative genomics

Singh D, Singh CK, Taunk J, Sharma S, Gaikwad K, Singh V, Sanwal SK, Singh D, Sharma PC, Pal M.
PMID: 33389259
Funct Integr Genomics. 2021 Jan;21(1):139-156. doi: 10.1007/s10142-020-00766-5. Epub 2021 Jan 03.

Extensive transcriptomic skimming was conducted to decipher molecular, morphological, physiological, and biochemical responses in salt-tolerant (PDL-1) and salt-sensitive (L-4076) cultivars under control (0 mM NaCl) and salinity stress (120 mM NaCl) conditions at seedling stage. Morphological, physiological, and biochemical...

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Singh D, Singh CK, Taunk J, et al. Transcriptome skimming of lentil (Lens culinaris Medikus) cultivars with contrast reaction to salt stress. Funct Integr Genomics. 2021;21(1):139-156doi: 10.1007/s10142-020-00766-5.
Singh, D., Singh, C. K., Taunk, J., Sharma, S., Gaikwad, K., Singh, V., Sanwal, S. K., Singh, D., Sharma, P. C., & Pal, M. (2021). Transcriptome skimming of lentil (Lens culinaris Medikus) cultivars with contrast reaction to salt stress. Functional & integrative genomics, 21(1), 139-156. https://doi.org/10.1007/s10142-020-00766-5
Singh, Dharmendra, et al. "Transcriptome skimming of lentil (Lens culinaris Medikus) cultivars with contrast reaction to salt stress." Functional & integrative genomics vol. 21,1 (2021): 139-156. doi: https://doi.org/10.1007/s10142-020-00766-5
Singh D, Singh CK, Taunk J, Sharma S, Gaikwad K, Singh V, Sanwal SK, Singh D, Sharma PC, Pal M. Transcriptome skimming of lentil (Lens culinaris Medikus) cultivars with contrast reaction to salt stress. Funct Integr Genomics. 2021 Jan;21(1):139-156. doi: 10.1007/s10142-020-00766-5. Epub 2021 Jan 03. PMID: 33389259.
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Microfluidic single-cell transcriptomics: moving towards multimodal and spatiotemporal omics.

Lab on a chip

Lin S, Liu Y, Zhang M, Xu X, Chen Y, Zhang H, Yang C.
PMID: 34541590
Lab Chip. 2021 Oct 12;21(20):3829-3849. doi: 10.1039/d1lc00607j.

Cells are the basic units of life with vast heterogeneity. Single-cell transcriptomics unveils cell-to-cell gene expression variabilities, discovers novel cell types, and uncovers the critical roles of cellular heterogeneity in biological processes. The recent advances in microfluidic technologies have...

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Lin S, Liu Y, Zhang M, et al. Microfluidic single-cell transcriptomics: moving towards multimodal and spatiotemporal omics. Lab Chip. 2021;21(20):3829-3849doi: 10.1039/d1lc00607j.
Lin, S., Liu, Y., Zhang, M., Xu, X., Chen, Y., Zhang, H., & Yang, C. (2021). Microfluidic single-cell transcriptomics: moving towards multimodal and spatiotemporal omics. Lab on a chip, 21(20), 3829-3849. https://doi.org/10.1039/d1lc00607j
Lin, Shichao, et al. "Microfluidic single-cell transcriptomics: moving towards multimodal and spatiotemporal omics." Lab on a chip vol. 21,20 (2021): 3829-3849. doi: https://doi.org/10.1039/d1lc00607j
Lin S, Liu Y, Zhang M, Xu X, Chen Y, Zhang H, Yang C. Microfluidic single-cell transcriptomics: moving towards multimodal and spatiotemporal omics. Lab Chip. 2021 Oct 12;21(20):3829-3849. doi: 10.1039/d1lc00607j. PMID: 34541590.
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Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host.

Nature communications

Lloréns-Rico V, Gregory AC, Van Weyenbergh J, Jansen S, Van Buyten T, Qian J, Braz M, Menezes SM, Van Mol P, Vanderbeke L, Dooms C, Gunst J, Hermans G, Meersseman P, Wauters E, Neyts J, Lambrechts D, Wauters J, Raes J.
PMID: 34716338
Nat Commun. 2021 Oct 29;12(1):6243. doi: 10.1038/s41467-021-26500-8.

Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the respiratory microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 respiratory...

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Lloréns-Rico V, Gregory AC, Van Weyenbergh J, et al. Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host. Nat Commun. 2021;12(1):6243doi: 10.1038/s41467-021-26500-8.
Lloréns-Rico, V., Gregory, A. C., Van Weyenbergh, J., Jansen, S., Van Buyten, T., Qian, J., Braz, M., Menezes, S. M., Van Mol, P., Vanderbeke, L., Dooms, C., Gunst, J., Hermans, G., Meersseman, P., Wauters, E., Neyts, J., Lambrechts, D., Wauters, J., & Raes, J. (2021). Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host. Nature communications, 12(1), 6243. https://doi.org/10.1038/s41467-021-26500-8
Lloréns-Rico, Verónica, et al. "Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host." Nature communications vol. 12,1 (2021): 6243. doi: https://doi.org/10.1038/s41467-021-26500-8
Lloréns-Rico V, Gregory AC, Van Weyenbergh J, Jansen S, Van Buyten T, Qian J, Braz M, Menezes SM, Van Mol P, Vanderbeke L, Dooms C, Gunst J, Hermans G, Meersseman P, Wauters E, Neyts J, Lambrechts D, Wauters J, Raes J. Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host. Nat Commun. 2021 Oct 29;12(1):6243. doi: 10.1038/s41467-021-26500-8. PMID: 34716338; PMCID: PMC8556379.
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Comparative physiological and transcriptomic analysis reveals salinity tolerance mechanisms in Sorghum bicolor (L.) Moench.

Planta

Ukwatta J, Pabuayon ICM, Park J, Chen J, Chai X, Zhang H, Zhu JK, Xin Z, Shi H.
PMID: 34657208
Planta. 2021 Oct 16;254(5):98. doi: 10.1007/s00425-021-03750-w.

MAIN CONCLUSION: Mota Maradi is a sorghum line that exhibits holistic salinity tolerance mechanisms, making it a viable potential donor in breeding efforts for improved sorghum lines. High soil salinity is one of the global challenges for crop growth...

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Ukwatta J, Pabuayon ICM, Park J, et al. Comparative physiological and transcriptomic analysis reveals salinity tolerance mechanisms in Sorghum bicolor (L.) Moench. Planta. 2021;254(5):98doi: 10.1007/s00425-021-03750-w.
Ukwatta, J., Pabuayon, I. C. M., Park, J., Chen, J., Chai, X., Zhang, H., Zhu, J. K., Xin, Z., & Shi, H. (2021). Comparative physiological and transcriptomic analysis reveals salinity tolerance mechanisms in Sorghum bicolor (L.) Moench. Planta, 254(5), 98. https://doi.org/10.1007/s00425-021-03750-w
Ukwatta, Jayan, et al. "Comparative physiological and transcriptomic analysis reveals salinity tolerance mechanisms in Sorghum bicolor (L.) Moench." Planta vol. 254,5 (2021): 98. doi: https://doi.org/10.1007/s00425-021-03750-w
Ukwatta J, Pabuayon ICM, Park J, Chen J, Chai X, Zhang H, Zhu JK, Xin Z, Shi H. Comparative physiological and transcriptomic analysis reveals salinity tolerance mechanisms in Sorghum bicolor (L.) Moench. Planta. 2021 Oct 16;254(5):98. doi: 10.1007/s00425-021-03750-w. PMID: 34657208.
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Transcriptomic Signature Differences Between SARS-CoV-2 and Influenza Virus Infected Patients.

Frontiers in immunology

Bibert S, Guex N, Lourenco J, Brahier T, Papadimitriou-Olivgeris M, Damonti L, Manuel O, Liechti R, Götz L, Tschopp J, Quinodoz M, Vollenweider P, Pagani JL, Oddo M, Hügli O, Lamoth F, Erard V, Voide C, Delorenzi M, Rufer N, Candotti F, Rivolta C, Boillat-Blanco N, Bochud PY.
PMID: 34135895
Front Immunol. 2021 May 31;12:666163. doi: 10.3389/fimmu.2021.666163. eCollection 2021.

The reason why most individuals with COVID-19 have relatively limited symptoms while other develop respiratory distress with life-threatening complications remains unknown. Increasing evidence suggests that COVID-19 associated adverse outcomes mainly rely on dysregulated immunity. Here, we compared transcriptomic profiles...

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Bibert S, Guex N, Lourenco J, et al. Transcriptomic Signature Differences Between SARS-CoV-2 and Influenza Virus Infected Patients. Front Immunol. 2021;12:666163doi: 10.3389/fimmu.2021.666163.
Bibert, S., Guex, N., Lourenco, J., Brahier, T., Papadimitriou-Olivgeris, M., Damonti, L., Manuel, O., Liechti, R., Götz, L., Tschopp, J., Quinodoz, M., Vollenweider, P., Pagani, J. L., Oddo, M., Hügli, O., Lamoth, F., Erard, V., Voide, C., Delorenzi, M., Rufer, N., Candotti, F., Rivolta, C., Boillat-Blanco, N., Bochud, P. Y. (2021). Transcriptomic Signature Differences Between SARS-CoV-2 and Influenza Virus Infected Patients. Frontiers in immunology, 12666163. https://doi.org/10.3389/fimmu.2021.666163
Bibert, Stéphanie, et al. "Transcriptomic Signature Differences Between SARS-CoV-2 and Influenza Virus Infected Patients." Frontiers in immunology vol. 12 (2021): 666163. doi: https://doi.org/10.3389/fimmu.2021.666163
Bibert S, Guex N, Lourenco J, Brahier T, Papadimitriou-Olivgeris M, Damonti L, Manuel O, Liechti R, Götz L, Tschopp J, Quinodoz M, Vollenweider P, Pagani JL, Oddo M, Hügli O, Lamoth F, Erard V, Voide C, Delorenzi M, Rufer N, Candotti F, Rivolta C, Boillat-Blanco N, Bochud PY. Transcriptomic Signature Differences Between SARS-CoV-2 and Influenza Virus Infected Patients. Front Immunol. 2021 May 31;12:666163. doi: 10.3389/fimmu.2021.666163. eCollection 2021. PMID: 34135895; PMCID: PMC8202013.
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Tripal v3: an ontology-based toolkit for construction of FAIR biological community databases.

Database : the journal of biological databases and curation

Spoor S, Cheng CH, Sanderson LA, Condon B, Almsaeed A, Chen M, Bretaudeau A, Rasche H, Jung S, Main D, Bett K, Staton M, Wegrzyn JL, Feltus FA, Ficklin SP.
PMID: 31328773
Database (Oxford). 2019 Jan 01;2019. doi: 10.1093/database/baz077.

Community biological databases provide an important online resource for both public and private data, analysis tools and community engagement. These sites house genomic, transcriptomic, genetic, breeding and ancillary data for specific species, families or clades. Due to the complexity...

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Spoor S, Cheng CH, Sanderson LA, et al. Tripal v3: an ontology-based toolkit for construction of FAIR biological community databases. Database (Oxford). 2019;2019doi: 10.1093/database/baz077.
Spoor, S., Cheng, C. H., Sanderson, L. A., Condon, B., Almsaeed, A., Chen, M., Bretaudeau, A., Rasche, H., Jung, S., Main, D., Bett, K., Staton, M., Wegrzyn, J. L., Feltus, F. A., & Ficklin, S. P. (2019). Tripal v3: an ontology-based toolkit for construction of FAIR biological community databases. Database : the journal of biological databases and curation, 2019. https://doi.org/10.1093/database/baz077
Spoor, Shawna, et al. "Tripal v3: an ontology-based toolkit for construction of FAIR biological community databases." Database : the journal of biological databases and curation vol. 2019 (2019). doi: https://doi.org/10.1093/database/baz077
Spoor S, Cheng CH, Sanderson LA, Condon B, Almsaeed A, Chen M, Bretaudeau A, Rasche H, Jung S, Main D, Bett K, Staton M, Wegrzyn JL, Feltus FA, Ficklin SP. Tripal v3: an ontology-based toolkit for construction of FAIR biological community databases. Database (Oxford). 2019 Jan 01;2019. doi: 10.1093/database/baz077. PMID: 31328773; PMCID: PMC6643302.
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Identification of Hub Genes Associated with Hypertension and Their Interaction with miRNA Based on Weighted Gene Coexpression Network Analysis (WGCNA) Analysis.

Medical science monitor : international medical journal of experimental and clinical research

Li Z, Chyr J, Jia Z, Wang L, Hu X, Wu X, Song C.
PMID: 32888289
Med Sci Monit. 2020 Sep 05;26:e923514. doi: 10.12659/MSM.923514.

BACKGROUND Hypertension is one of the most widespread health conditions in the world, and the molecular mechanism of it is still unclear. In this study, we identified the hub genes (hub miRNA genes) associated with hypertension and explored the...

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Li Z, Chyr J, Jia Z, et al. Identification of Hub Genes Associated with Hypertension and Their Interaction with miRNA Based on Weighted Gene Coexpression Network Analysis (WGCNA) Analysis. Med Sci Monit. 2020;26:e923514doi: 10.12659/MSM.923514.
Li, Z., Chyr, J., Jia, Z., Wang, L., Hu, X., Wu, X., & Song, C. (2020). Identification of Hub Genes Associated with Hypertension and Their Interaction with miRNA Based on Weighted Gene Coexpression Network Analysis (WGCNA) Analysis. Medical science monitor : international medical journal of experimental and clinical research, 26e923514. https://doi.org/10.12659/MSM.923514
Li, Zongjin, et al. "Identification of Hub Genes Associated with Hypertension and Their Interaction with miRNA Based on Weighted Gene Coexpression Network Analysis (WGCNA) Analysis." Medical science monitor : international medical journal of experimental and clinical research vol. 26 (2020): e923514. doi: https://doi.org/10.12659/MSM.923514
Li Z, Chyr J, Jia Z, Wang L, Hu X, Wu X, Song C. Identification of Hub Genes Associated with Hypertension and Their Interaction with miRNA Based on Weighted Gene Coexpression Network Analysis (WGCNA) Analysis. Med Sci Monit. 2020 Sep 05;26:e923514. doi: 10.12659/MSM.923514. PMID: 32888289; PMCID: PMC7491244.
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