Publications by authors named "T R Murali"

Motivation: Molecular interaction networks are powerful tools for studying cellular functions. Integrating diverse types of networks enhances performance in downstream tasks such as gene module detection and protein function prediction. The challenge lies in extracting meaningful protein feature representations due to varying levels of sparsity and noise across these heterogeneous networks.

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Sex differences in melanoma are prominent, with females having a significant survival advantage. However, it is unclear why we see this survival advantage. Here we investigate the relationship between sex, clinicopathologic variables, and melanoma specific survival in 1,753 single primary melanomas from patients in the GEM study.

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Donor-specific antibodies (DSAs) targeting mismatched human leukocyte antigen (HLA) molecules are one of the principal threats to long-term graft survival in solid organ transplantation. However, many patients with long-term circulating DSAs do not manifest rejection responses, suggesting a degree of heterogeneity in their pathogenicity and related functional activity. Immunologic risk stratification of transplant recipients is complicated by challenges intrinsic to defining alloantibody responses that are potentially pathogenic versus those that are not.

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(PA), an opportunistic human pathogen that is frequently linked with chronic infections in immunocompromised individuals, is also metabolically versatile, and thrives in diverse environments. Additionally, studies report that PA can interact with other microorganisms, such as bacteria, and fungi, producing unique metabolites that can modulate the host immune response, and contribute to disease pathogenesis. This review summarizes the current knowledge related to the metabolic interactions of PA with other microorganisms (, , , , and ) and human hosts, and the importance of these interactions in a polymicrobial context.

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Article Synopsis
  • Network biology is an interdisciplinary field that combines computational and biological sciences to improve understanding of cellular functions and diseases, though it is still a developing area after two decades.* -
  • The field faces challenges due to the increasing complexity and diversity of biological data, but active research areas include molecular networks, patient similarity networks, and machine learning applications.* -
  • The article provides an overview of recent advancements, highlights future directions, and emphasizes the need for diverse scientific communities and educational initiatives within network biology.*
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