Bioinformatics Studies of Human Viruses

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We developed a statistical method summarizing the mutational patterns in HIV sequences from early infection. We showed that the summary agreed with simulation results for an HIV population during early infection in a single host. We have also showed that to useful accuracies in feasible experimental designs, we can reconstruct features of the early population growth of an HIV infection in a single host. With an NCI collaborator, Dr Ziegelbauer, we previously reported on a statistical method that we developed for inferring whether herpesvirus miRNA motifs were overrepresented on human circular RNAs. We have refined and generalized the computer algorithm for the method to other biological situations where one wants to infer that one of the terms of a sum is "too large", e.g., whether a human circular RNA has "too many" instances of a herpesvirus miRNA motif relative to other circular RNAs, whether a particular column of a domain alignments from cancer patients contains "too many" mutations, etc. We have automated the calculation of the Malthusian parameter controlling the initial exponential growths of the COVID-19 epidemic in many countries. A basic formula from Wallinga & Lipsitch relates the basic reproduction number R0 of the COVID-19 to the Malthusian parameter.