GeniePool 2.0: advancing variant analysis through CHM13-T2T, AlphaMissense, gnomAD V4 integration, and variant co-occurrence queries.

Originally developed to meet the challenges of genomic data deluge, GeniePool emerged as a pioneering platform, enabling efficient storage, accessibility, and analysis of vast genomic datasets, enabled due to its data lake architecture. Building on this foundation, GeniePool 2.0 advances genomic analysis through the integration of cutting-edge variant databases, such as CHM13-T2T, AlphaMissense, and gnomAD V4, coupled with the capability for variant co-occurrence queries.

GeniePool: genomic database with corresponding annotated samples based on a cloud data lake architecture.

In recent years, there are a huge influx of genomic data and a growing need for its phenotypic correlations, yet existing genomic databases do not allow easy storage and accessibility to the combined phenotypic-genotypic information. Freely accessible allele frequency (AF) databases, such as gnomAD, are crucial for evaluating variants but lack correlated phenotype data. The Sequence Read Archive (SRA) accumulates hundreds of thousands of next-generation sequencing (NGS) samples tagged by their submitters and various attributes.

Coordinating Amoebots via Reconfigurable Circuits.

We consider an extension to the geometric amoebot model that allows amoebots to form so-called . Given a connected amoebot structure, a circuit is a subgraph formed by the amoebots that permits the instant transmission of signals. We show that such an extension allows for significantly faster solutions to a variety of problems related to programmable matter.

Design of nanorobots for exposing cancer cells.

We discuss in detail, the design of a nanorobot that can navigate, detect cancer cells in the blood and actuate the exposure of drugs. The nanorobot is designed with blood energy harvesting capability and the accumulation of electricity in a capacitor, which forms the main body of the nanorobot. Glucose hunger-based cancer detectors immobilized on a carbon nanotube sensor, reduces its electrical resistance when attached to a cancer cell.

Towards holographic "brain" memory based on randomization and Walsh-Hadamard transformation.

The holographic conceptual approach to cognitive processes in the human brain suggests that, in some parts of the brain, each part of the memory (a neuron or a group of neurons) contains some information regarding the entire data. In Dolev and Frenkel (2010, 2012) we demonstrated how to encode data in a holographic manner using the Walsh-Hadamard transform. The encoding is performed on randomized information, that is then represented by a set of Walsh-Hadamard coefficients.

Graph degree sequence solely determines the expected hopfield network pattern stability.

We analyze the effect of network topology on the pattern stability of the Hopfield neural network in the case of general graphs. The patterns are randomly selected from a uniform distribution. We start the Hopfield procedure from some pattern v.

Optical solver of combinatorial problems: nanotechnological approach.

We present an optical computing system to solve NP-hard problems. As nano-optical computing is a promising venue for the next generation of computers performing parallel computations, we investigate the application of submicron, or even subwavelength, computing device designs. The system utilizes a setup of exponential sized masks with exponential space complexity produced in polynomial time preprocessing.

High-speed and low-power electro-optical DSP coprocessor.

A fast, power-efficient electro-optical vector-by-matrix multiplier (VMM) architecture is presented. Careful design of an electrical unit supporting high-speed data transfer enables this architecture to overcome bottlenecks encountered by previous VMM architectures. Based on the proposed architecture, we present an electro-optical digital signal processing (DSP) coprocessor that can achieve a significant speedup of 2-3 orders of magnitude over existing DSP technologies and execute more than 16 teraflops.

Optical high-performance computing: introduction to the JOSA A and Applied Optics feature.

The feature issues in both Applied Optics and the Journal of the Optical Society of America A focus on topics of immediate relevance to the community working in the area of optical high-performance computing.

Fast algorithm for successive computation of group betweenness centrality.

In this paper, we propose a method for rapid computation of group betweenness centrality whose running time (after preprocessing) does not depend on network size. The calculation of group betweenness centrality is computationally demanding and, therefore, it is not suitable for applications that compute the centrality of many groups in order to identify new properties. Our method is based on the concept of path betweenness centrality defined in this paper.

Optical solution for bounded NP-complete problems.

We present a new optical method for solving bounded (input-length-restricted) NP-complete combinatorial problems. We have chosen to demonstrate the method with an NP-complete problem called the traveling salesman problem (TSP). The power of optics in this method is realized by using a fast matrix-vector multiplication between a binary matrix, representing all feasible TSP tours, and a gray-scale vector, representing the weights among the TSP cities.