Publikationen von A Gautam

Fiori da Silva, G.; Gautam, A.; Silveira Duarte, I.; Palladino Delforno, T.; Delforno, T.; Maia de Oliveira, V.; Huson, D.: Interactive analysis of biosurfactants in fruit-waste fermentation samples using BioSurfDB and MEGAN. Scientific Reports 12, 7769 (2022)

Gautam, A.; Felderhoof, H.; Bağci, C.; Huson, D.: Using AnnoTree to Get More Assignments, Faster, in DIAMOND+MEGAN Microbiome Analysis. mSystems 7 (1), e0140821 (2022)

Ghosh, A.; Kar, P.; Gautam, A.; Gupta, R.; Singh, R.; Chakravarti, R.; Ravichandiran, V.; Dastidar, S.; Ghosh, D.; Roy, S.: An insight into SARS-CoV-2 structure, pathogenesis, target hunting for drug development and vaccine initiatives. RSC Medicinal Chemistry 13 (6), S. 647 - 675 (2022)

Chandel, S.; Singh, R.; Gautam, A.; Ravichandiran, V.: Screening of Azadirachta indica phytoconstituents as GSK-3β inhibitor and its implication in neuroblastoma: molecular docking, molecular dynamics, MM-PBSA binding energy, and in-vitro study. Journal of Biomolecular Structure and Dynamics 40 (23), S. 12827 - 12840 (2021)

Banerjee, R.; Chaudhari, N.; Lahiri, A.; Gautam, A.; Bhowmik, D.; Dutta, C.; Chattopadhyay, S.; Huson, D.; Paul, S.: Interplay of Various Evolutionary Modes in Genome Diversification and Adaptive Evolution of the Family Sulfolobaceae. Frontiers in Microbiology 12, 639995 (2021)

Singh, R.; Gautam, A.; Chandel, S.; Sharma, V.; Ghosh, A.; Dey, D.; Roy, S.; Ravichandiran, V.; Ghosh, D.: Computational screening of FDA approved drugs of fungal origin that may interfere with SARS-CoV-2 spike protein activation, viral RNA replication, and post-translational modification: a multiple target approach. In Silico Pharmacology 9 (1), 27 (2021)

Weng, C.; Gautam, A.; Huson, D.: On the Application of Advanced Machine Learning Methods to Analyze Enhanced, Multimodal Data from Persons Infected with COVID-19. Computation 9, 4 (2021)

Singh, R.; Gautam, A.; Chandel, S.; Ghosh, A.; Dey, D.; Roy, S.; Ravichandiran, V.; Ghosh, D.: Protease Inhibitory Effect of Natural Polyphenolic Compounds on SARS-CoV-2: An In Silico Study. Molecules 25 (20), 4604 (2020)

Chaudhari, N.; Gautam, A.; Gupta, V.; Kaur, G.; Dutta, C.; Paul, S.: PanGFR-HM: A Dynamic Web Resource for Pan-Genomic and Functional Profiling of Human Microbiome With Comparative Features. Frontiers in Microbiology 9, 2322 (2018)

Gautam, A.; Zeng, W.; Huson, D.: DIAMOND + MEGAN Microbiome Analysis. In: Metagenomic Data Analysis, S. 107 - 131 (Hg. Mitra, S.). Humana Press, NewYork, NY, USA (2023)

Kumar, K.; Bhowmik, D.; Mandloi, S.; Gautam, A.; Lahiri, A.; Biswas, N.; Paul, S.; Chakrabarti, S.: Integrating Multi-Omics Data to Construct Reliable Interconnected Models of Signaling, Gene Regulatory, and Metabolic Pathways. In: Computational Modeling of Signaling Networks, S. 139 - 151 (Hg. Nguyen, L.). Humana, New York, NY, USA (2023)

Gautam, A.; Huson, D.: Using BinAC to analyze microbiome samples. In: 8th bwHPC Symposium, S. 7 - 17 (Hg. Weyers, C.-M.). 8th bwHPC Symposium, 28. November 2022. (2022)

Botta, C.; Tsoureki, D.; Gautam, A.; Patz, S.; Pissaridi, K.; Ferrocino, I.; Franciosa, I.; Cocolin, L.; Huson, D.; Rantsiou, K.: How can DNA-based omics effectively improve microbiological quality control? An explorative study applied to infant food production. In 28th ICFMH International Conference: FoodMicro 2024, 4.4, S. 62 - 63. 28th ICFMH International Conference: FoodMicro 2024, Burgos, Spain, 08. Juli 2024 - 11. Juli 2024. (2024)

Botta, C.; Tsoureki, D.; Gautam, A.; Patz, S.; Pissaridi, K.; Ferrocino, I.; Cocolin, L.; Huson, D.; Rantsiou, K.: The pros and cons of tracking the microbial contamination in infant food processing chain through amplicon sequencing and metagenomics. In Food System Microbiomes 2024, S5-ST03, S. 50. Food System Microbiomes 2024, Torino, Italy, 14. Mai 2024 - 17. Mai 2024. (2024)

Gautam, A.: Using AnnoTree to Get More Assignments, Faster, in DIAMOND+MEGAN Microbiome Analysis. In 31st Annual Intelligent Systems For Molecular Biology and the 22nd Annual European Conference on Computational Biology (ISMB/ECCB 2023). 31st Annual Intelligent Systems For Molecular Biology and the 22nd Annual European Conference on Computational Biology (ISMB/ECCB 2023), Lyon, France, 23. Juli 2023 - 27. Juli 2023. (2023)

Patz, S.; Gautam, A.; Becker, M.; Ruppel, S.; Huson, D.: From application of the plant growth-promoting traits ontology towards a sustainable plant production. In Molecular Plant-Microbe Interactions, 32 (3 Supplement), S. 4. 2021 IS-MPMI Congress: Plant–Microbe Interactions in the Environment: Navigating a Complex World, 01. Dezember 2021 - 02. Dezember 2021. APS Press, St. Paul, MN, USA (2021)

Gautam, A.: Breaking the wall of metagenomic computation. Falling Walls Lab Berlin-Adlershof , Berlin, Germany (2024)

Huson, D.; Gautam, A.; Zeng, W.: Tutorial IP6: Interactive microbiome analysis using DIAMOND+MEGAN. 31st Conference on Intelligent Systems for Molecular Biology and 22nd European Conference on Computational Biology (ISMB/ECCB 2023), Lyon, France (2023)

Gautam, A.; Bhowmik, D.; Basu, S.; Zeng, W.; Lahiri, A.; Huson, D.; Paul, S.: Microbiome Metabolome Integration Platform (MMIP): a web-based platform for microbiome and metabolome data integration and feature identification. 3rd International Conference Controlling Microbes to Fight Infections (CMFI 2023), Tübingen, Germany (2023)

Gautam, A.: Advancing Microbial and Metagenomic Analysis through Computational Tools and Integrated Data Systems. Dissertation, Eberhard-Karls-Universität, Tübingen, Germany (2025)