Mash extends the MinHash dimensionality-reduction technique to include a pairwise mutation distance and P value significance test, enabling the efficient clustering and search of massive sequence collections. Mash reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated. We demonstrate several use cases, including the clustering of all 54,118 NCBI RefSeq genomes in 33 CPU h; real-time database search using assembled or unassembled Illumina, Pacific Biosciences, and Oxford Nanopore data; and the scalable clustering of hundreds of metagenomic samples by composition. Mash is freely released under a BSD license (
 https://github.com/marbl/mash
 ).

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Mash: fast genome and metagenome distance estimation using MinHash.

In this article, we give an overview of efficient algorithms for the approximate and exact nearest neighbor problem. The goal is to preprocess a dataset of objects (e.g., images) so that later, given a new query object, one can quickly return the dataset object that is most similar to the query. The problem is of significant interest in a wide variety of areas.

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Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions

This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way. The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds. All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.

Parameterized Algorithms

We present an algorithm for the c-approximate nearest neighbor problem in a d-dimensional Euclidean space, achieving query time of O\left( {dn^{1/c^2 + o(1)} } \right) and space O\left( {dn + n^{1 + 1/c^2 + o(1)} } \right). This almost matches the lower bound for hashing-based algorithm recently obtained in [27]. We also obtain a space-efficient version of the algorithm, which uses dn+n log^{O(1)} n space, with a query time of dn^{O(1/c^2 )}. Finally, we discuss practical variants of the algorithms that utilize fast bounded-distance decoders for the Leech Lattice.

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Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions

We present two algorithms for the approximate nearest neighbor problem in high dimensional spaces. For data sets of size n living in IR, the algorithms require space that is only polynomial in n and d, while achieving query times that are sub-linear in n and polynomial in d. We also show applications to other high-dimensional geometric problems, such as the approximate minimum spanning tree.

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Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality

Design, fabrication and characterization of electrostatic micro actuators for microfluidic platforms

A microfluidic device is described. The microfluidic device comprises at least one transport channel and at least one working chamber, wherein the at least one transport channel and the at least one working chamber are separated from each other by a common deformable wall. The at least one transport channel is for containing a transport fluid and the at least one working chamber is for containing a working fluid. The microfluidic device comprises at least one pair of electrodes for changing the pressure on the working fluid such that when the pressure on the working fluid is changed, the deformable wall deforms, resulting in a change of the cross-section of the at least one transport channel. The working chamber comprises a flexible wall different from the common deformable wall and at least one electrode of the at least one pair of electrodes is provided on the flexible wall.

Microfluidic-device systems and methods for manufacturing microfluidic-device systems

We present algorithms for computing ranks and order statistics in the Farey sequence, taking time O (n^{2/3}). This improves on the recent algorithms of Pawlewicz [European Symp. Alg. 2007], running in time O (n^{3/4}). We also initiate the study of a more general algorithmic problem: counting primitive lattice points in planar shapes.

Farey Statistics in Time n^{2/3} and Counting Primitive Lattice Points in Polygons

The study of fluid flow in micro systems is still an open issue Finite element models are generally used during prototyping Such models are useful when the geometry has a large impact on device performance Unfortunately, the nature of such methods and especially the mesh complexity limits simulation studies to non-transient or limited transient behavior We present a different approach of microfluidic modeling, which is based on bond graph theory Lumped component physics and power relations between the elements determine the dynamic behavior In this way, dynamic simulations are ubiquitous and pave a way for control design After introducing a number of basic microfluidic components, we concentrate on a case consisting of a three-valve micropump actuated peristaltically and connected to a thin, long tube Input signals, device dimensions, electrical and mechanical material properties and fluid viscosity are explicitly present in the model and can be fitted for increased performance Amongst others, simulations reveal the volume flow, pressure generation, and average fluid velocity throughout the modelCopyright © 2007 by ASME

Mihai Patrascu

Papers

Design, fabrication and characterization of electrostatic micro actuators for microfluidic platforms

Microfluidic-device systems and methods for manufacturing microfluidic-device systems

Farey Statistics in Time n^{2/3} and Counting Primitive Lattice Points in Polygons

Novel Approach for Physical Modeling of Microfluidic Systems

Physical modelling of the μWalker, a MEMS linear stepper actuator