Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review.

Background: Network medicine is an emerging area of research that focuses on delving into the molecular complexity of the disease, leading to the discovery of network biomarkers and therapeutic target discovery. Amyotrophic lateral sclerosis (ALS) is a complicated rare disease with unknown pathogenesis and no available treatment. In ALS, network properties appear to be potential biomarkers that can be beneficial in disease-related applications when explored independently or in tandem with machine learning (ML) techniques.

The SARS-CoV-2 targeted human RNA binding proteins network biology to investigate COVID-19 associated manifestations.

The global coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-CoV-2 virus has had unprecedented social and economic ramifications. Identifying targets for drug repurposing could be an effective means to present new and fast treatments. Furthermore, the risk of morbidity and mortality from COVID-19 goes up when there are coexisting medical conditions, however, the underlying mechanisms remain unclear.

Multi-stage transcriptome profiling of the neglected food-borne echinostome Artyfechinostomum sufrartyfex reveal potential diagnostic and drug targets.

Lack of effective surveillance and control methods for neglected helminth diseases particularly in context of rural areas in India is a serious concern in terms of public health. With regard to the emerging food-borne echinostomid Artyfechinostomum sufrartyfex infection in the country, the current study is an in silico attempt to screen for plausible diagnostic and drug targets against the trematode. Transcriptome of adult, encysted and excysted metacercaria stages of the parasite was generated using Illumina sequencing platform.

Variety-specific transcript accumulation during reproductive stage in drought-stressed rice.

The divergence of natural stress tolerance mechanisms between species is an intriguing phenomenon. To study it in rice, a comparative transcriptome analysis was carried out in 'heading' stage tissue (flag leaf, panicles and roots) of Nagina 22 (N22; drought-tolerant) and IR64 (drought-sensitive) plants subjected to field drought. Interestingly, N22 showed almost double the number of differentially expressed genes (DEGs) than IR64.

Manually curated database of rice proteins.

'Manually Curated Database of Rice Proteins' (MCDRP) available at http://www.genomeindia.org/biocuration is a unique curated database based on published experimental data.