Graph networks can model the data observed across different levels of biological systems that span from the population graph (with patients as network nodes) to the molecular graphs that involve omics data. Graph-based approaches have shed light on decoding biological processes modulated by complex interactions. This paper systematically reviews the graph-based analysis methods, including Graph Signal Processing (GSP), Graph Neural Network (GNN), and graph topology inference methods, and their applications to biological data. This work focuses on the algorithms of the graph-based approaches and the constructions of the graph-based frameworks that are adapted to the broad range of biological data. We cover the Graph Fourier Transform and the graph filter developed in GSP, which provides tools to investigate biological networks in the graph domain that can potentially benefit from the underlying graph structure. We also review the node, graph, and interaction oriented GNN architecture with inductive and transductive learning manners for various biological objectives. As the key component of graph analysis, we provide a review of the graph topology inference methods that incorporate assumptions for specific biological objectives. Finally, we discuss the biological application of graph analysis methods within the exhaustive literature collection, potentially providing insights for future research in the biological sciences.

Epilepsy is a common chronic consequence of traumatic brain injury (TBI), contributing to increased morbidity and mortality for survivors. As post-traumatic epilepsy (PTE) is drug-resistant in at least one-third of patients, there is a clear need for novel therapeutic strategies to prevent epilepsy from developing after TBI, or to mitigate its severity. It has long been recognized that seizure activity is associated with a local immune response, characterized by the activation of microglia and astrocytes and the release of a plethora of pro-inflammatory cytokines and chemokines. More recently, increasing evidence also supports a causal role for neuroinflammation in seizure induction and propagation, acting both directly and indirectly on neurons to promote regional hyperexcitability. In this narrative review, we focus on key aspects of the neuroinflammatory response that have been implicated in epilepsy, with a particular focus on PTE. The contributions of glial cells, blood-derived leukocytes, and the blood–brain barrier will be explored, as well as pro- and anti-inflammatory mediators. While the neuroinflammatory response to TBI appears to be largely pro-epileptogenic, further research is needed to clearly demonstrate causal relationships. This research has the potential to unveil new drug targets for PTE, and identify immune-based biomarkers for improved epilepsy prediction.

There is a growing body of clinical and experimental evidence that neurodegenerative diseases and epileptogenesis after an acquired brain insult may share common etiological mechanisms. Acquired epilepsy commonly develops as a comorbid condition in patients with neurodegenerative diseases such as Alzheimer's disease, although it is likely much under diagnosed in practice. Progressive neurodegeneration has also been described after traumatic brain injury, stroke, and other forms of brain insults. Moreover, recent evidence has shown that acquired epilepsy is often a progressive disorder that is associated with the development of drug resistance, cognitive decline, and worsening of other neuropsychiatric comorbidities. Therefore, new pharmacological therapies that target neurobiological pathways that underpin neurodegenerative diseases have potential to have both an anti‐epileptogenic and disease‐modifying effect on the seizures in patients with acquired epilepsy, and also mitigate the progressive neurocognitive and neuropsychiatric comorbidities. Here, we review the neurodegenerative pathways that are plausible targets for the development of novel therapies that could prevent the development or modify the progression of acquired epilepsy, and the supporting published experimental and clinical evidence.