Multi-input multi-output (MIMO) frequency-modulated continuous-wave (FMCW) radar can sense minute body motions, enabling non-contact vital-sign monitoring for applications such as sleep tracking, elderly care, and healthcare. While conventional radar imaging can localize multiple targets, it is limited in distinguishing human subjects from surrounding clutter. In this work, a vital-sign detection and clutter discrimination method using a 77-GHz MIMO FMCW radar is proposed. Range–Doppler maps are constructed by applying a two-dimensional fast Fourier transform (2D FFT) along the fast-time (range) and slow-time (Doppler) dimensions, revealing low-frequency micro-Doppler signatures induced by respiration and heartbeat. Simulations verify that the proposed approach effectively separates human targets from static clutter, and experimental validation using a real radar prototype confirms consistent performance in practical environments. The results demonstrate reliable extraction of vital-sign components and robust human–clutter discrimination, highlighting the feasibility of the method for non-contact bio-sensing applications.

MOTIVATION: Proteogenomics has proven its utility by integrating genomics and proteomics. Typical approaches use data from next-generation sequencing to infer proteins expressed. A sample-specific protein sequence database is often adopted to identify novel peptides from matched mass spectrometry-based proteomics; nevertheless, there is no software that can practically identify all possible forms of mutated peptides suggested by various genomic information sources. RESULTS: We propose MutCombinator, which enables us to practically identify mutated peptides from tandem mass spectra allowing combinatorial mutations during the database search. It uses an upgraded version of a variant graph, keeping track of frame information. The variant graph is indexed by nine nucleotides for fast access. Using MutCombinator, we could identify more mutated peptides than previous methods, because combinations of point mutations are considered and also because it can be practically applied together with a large mutation database such as COSMIC. Furthermore, MutCombinator supports in-frame search for coding regions and three-frame search for non-coding regions. AVAILABILITY AND IMPLEMENTATION: https://prix.hanyang.ac.kr/download/mutcombinator.jsp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Summary: In many proteogenomic applications, mapping peptide sequences onto genome sequences can be very useful, because it allows us to understand origins of the gene products. Existing software tools either take the genomic position of a peptide start site as an input or assume that the peptide sequence exactly matches the coding sequence of a given gene model. In case of novel peptides resulting from genomic variations, especially structural variations such as alternative splicing, these existing tools cannot be directly applied unless users supply information about the variant, either its genomic position or its transcription model. Mapping potentially novel peptides to genome sequences, while allowing certain genomic variations, requires introducing novel gene models when aligning peptide sequences to gene structures. We have developed a new tool called ACTG (Amino aCids To Genome), which maps peptides to genome, assuming all possible single exon skipping, junction variation allowing three edit distances from the original splice sites, exon extension and frame shift. In addition, it can also consider SNVs (single nucleotide variations) during mapping phase if a user provides the VCF (variant call format) file as an input. Availability and Implementation: Available at http://prix.hanyang.ac.kr/ACTG/search.jsp . Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.