Journal: Journal of Cheminformatics

Article Title: Software platform virtualization in chemistry research and university teaching

doi: 10.1186/1758-2946-1-18

Figure Lengend Snippet: List of system statistics and micro-benchmarks comparing an original Windows XP performance and Windows XP inside a virtual machine (Guest OS).

Article Snippet: The single core benchmarks NIST SciMark 2.0a, Molgen Demo, CDK Descriptor GUI, Seven Golden Rules are all single-threaded benchmarks.

Techniques:

Journal: Bioinformatics

Article Title: The K-mer File Format: a standardized and compact disk representation of sets of k -mers

doi: 10.1093/bioinformatics/btac528

Figure Lengend Snippet: Comparison of file sizes (in GB) for several techniques for storing 32-mers on disk: naive plain-text encoding (‘T’), KMC file format (‘KMC’), KFF file format storing one k -mer per block (‘KFF+naive’) or storing super- k -mers as created by kmtricks (‘KFF+sk’), or using k -mers stored as a string-preserving string set (’KFF+SPSS’)

Article Snippet: In terms of running times, on the Gallus dataset using 8 threads, KMC took 9 min, KFF+sk 113 min and KFF+SPSS 900 single-threaded minutes (optimization pending).

Techniques: Comparison, Blocking Assay

Journal: BMC Bioinformatics

Article Title: BarWare: efficient software tools for barcoded single-cell genomics

doi: 10.1186/s12859-022-04620-2

Figure Lengend Snippet: Implementation of BarCounter and BarMixer. A Trie data structures are used in BarCounter to efficiently tabulate barcode frequencies. B Diagram of HTO read structure. Read 1 contains the 16 bp cell barcode and the 12 bp UMI. Read 2 contains the 15 bp hashtag. C Overview of the BarCounter workflow. At runtime, the user provides a barcode whitelist which is loaded into a trie for rapid lookups, a taglist containing all valid hashtag sequences, and paired Read 1 and Read 2 FASTQ files. For each read, checks are performed to verify the cell barcode exists in the barcode trie, and the hashtag sequence is in the taglist. The UMI sequence is checked against a trie and if it is not present, the trie is updated and the counts for the barcode and hashtag combination are incremented. D–F Benchmarking comparisons of BarCounter and other available HTO counting algorithms as a function of increasing cell loading per 10x Genomics well: cellranger count (10x Genomics); CITE-seq-Count (with or without barcode correction, , KITE, (single-threaded or with 8 threads). D Maximum memory usage, E Average CPU load, F Elapsed time. G Overview of the barcode cutoff determination method used by BarMixer: Raw counts generated by BarCounter are clipped to remove low values, then log transformed, and used as input to 2-cluster K-means. If cluster medians are separable, the cutoff is set to the lowest value in the positive cluster. Note broken y-axis in the first two panels. H–L Visualizations provided by BarMixer QC reporting notebooks. H HTO count histograms (green bars) with cutoff values (blue lines), I Fractions of barcodes and reads attributed to singlets (dark blue), doublets (light blue), and multiplets (purple), J Counts of cells in each hashing category per well in a batch, K Number of UMIs per cell in each HTO category, L Number of genes per cell in each HTO category

Article Snippet: D–F Benchmarking comparisons of BarCounter and other available HTO counting algorithms as a function of increasing cell loading per 10x Genomics well: cellranger count (10x Genomics); CITE-seq-Count (with or without barcode correction, [ ], KITE, [ ] (single-threaded or with 8 threads).

Techniques: Sequencing, Generated, Transformation Assay

Journal: BMC Research Notes

Article Title: Fast reconstruction of 3D volumes from 2D CT projection data with GPUs

doi: 10.1186/1756-0500-7-582

Figure Lengend Snippet: Performance of different implementations (in seconds)

Article Snippet: We have implemented the FDK algorithm from this toolbox using several different methods including single threaded code written in C, parallel code written in C with OpenMP constructs, parallel code in MATLAB using the parallel computing toolbox (PCT) and GPU codes written in CUDA-C and OpenCL.

Techniques: