Biomedical subjects

Ranit Aharonov

Publications and source records attributed to Ranit Aharonov.

5 recordsLinked to original sources

PubMed2005

Identification of hundreds of conserved and nonconserved human microRNAs.

MicroRNAs are noncoding RNAs of approximately 22 nucleotides that suppress translation of target genes by binding to their mRNA and thus have a central role in gene regulation in health and disease. To date, 222 human microRNAs have been identified, 86 by random cloning and sequencing, 43 by computational approaches and the rest as putative microRNAs homologous to microRNAs in other species. To prove our hypothesis that the total number of microRNAs may be much larger and that several have emerged only in primates, we developed an integrative approach combining bioinformatic predictions with microarray analysis and sequence-directed cloning. Here we report the use of this approach to clone and sequence 89 new human microRNAs (nearly doubling the current number of sequenced human microRNAs), 53 of which are not conserved beyond primates. These findings suggest that the total number of human microRNAs is at least 800.

Base Sequence↗

PubMed2005

Dynamic model of the octopus arm. I. Biomechanics of the octopus reaching movement.

The octopus arm requires special motor control schemes because it consists almost entirely of muscles and lacks a rigid skeletal support. Here we present a 2D dynamic model of the octopus arm to explore possible strategies of movement control in this muscular hydrostat. The arm is modeled as a multisegment structure, each segment containing longitudinal and transverse muscles and maintaining a constant volume, a prominent feature of muscular hydrostats. The input to the model is the degree of activation of each of its muscles. The model includes the external forces of gravity, buoyancy, and water drag forces (experimentally estimated here). It also includes the internal forces generated by the arm muscles and the forces responsible for maintaining a constant volume. Using this dynamic model to investigate the octopus reaching movement and to explore the mechanisms of bend propagation that characterize this movement, we found the following. 1) A simple command producing a wave of muscle activation moving at a constant velocity is sufficient to replicate the natural reaching movements with similar kinematic features. 2) The biomechanical mechanism that produces the reaching movement is a stiffening wave of muscle contraction that pushes a bend forward along the arm. 3) The perpendicular drag coefficient for an octopus arm is nearly 50 times larger than the tangential drag coefficient. During a reaching movement, only a small portion of the arm is oriented perpendicular to the direction of movement, thus minimizing the drag force.

Animals↗

PubMed2004

MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues.

MicroRNAs (MIRs) are a novel group of conserved short approximately 22 nucleotide-long RNAs with important roles in regulating gene expression. We have established a MIR-specific oligonucleotide microarray system that enables efficient analysis of the expression of the human MIRs identified so far. We show that the 60-mer oligonucleotide probes on the microarrays hybridize with labeled cRNA of MIRs, but not with their precursor hairpin RNAs, derived from amplified, size-fractionated, total RNA of human origin. Signal intensity is related to the location of the MIR sequences within the 60-mer probes, with location at the 5' region giving the highest signals, and at the 3' end, giving the lowest signals. Accordingly, 60-mer probes harboring one MIR copy at the 5' end gave signals of similar intensity to probes containing two or three MIR copies. Mismatch analysis shows that mutations within the MIR sequence significantly reduce or eliminate the signal, suggesting that the observed signals faithfully reflect the abundance of matching MIRs in the labeled cRNA. Expression profiling of 150 MIRs in five human tissues and in HeLa cells revealed a good overall concordance with previously published results, but also with some differences. We present novel data on MIR expression in thymus, testes, and placenta, and have identified MIRs highly enriched in these tissues. Taken together, these results highlight the increased sensitivity of the DNA microarray over other methods for the detection and study of MIRs, and the immense potential in applying such microarrays for the study of MIRs in health and disease.

Base Sequence↗

PubMed2003

Localization of function via lesion analysis.

This article presents a general approach for employing lesion analysis to address the fundamental challenge of localizing functions in a neural system. We describe functional contribution analysis (FCA), which assigns contribution values to the elements of the network such that the ability to predict the network's performance in response to multilesions is maximized. The approach is thoroughly examined on neurocontroller networks of evolved autonomous agents. The FCA portrays a stable set of neuronal contributions and accurate multilesion predictions that are significantly better than those obtained based on the classical single lesion approach. It is also used for a detailed synaptic analysis of the neurocontroller connectivity network, delineating its main functional backbone. The FCA provides a quantitative way of measuring how the network functions are localized and distributed among its elements. Our results question the adequacy of the classical single lesion analysis traditionally used in neuroscience and show that using lesioning experiments to decipher even simple neuronal systems requires a more rigorous multilesion analysis.

Algorithms↗

PubMed2003

High-dimensional analysis of evolutionary autonomous agents.

This article presents a new approach to the important challenge of localizing function in a neurocontroller. The approach is based on the basic functional contribution analysis (FCA) presented earlier, which assigns contribution values to the elements of the network, such that the ability to predict the network's performance in response to multi-unit lesions is maximized. These contribution values quantify the importance of each element to the tasks the agent performs. Here we present a generalization of the basic FCA to high-dimensional analysis, using high-order compound elements. Such elements are composed of conjunctions of simple elements. Their usage enables the explicit expression of sets of neurons or synapses whose contributions are interdependent, a prerequisite for localizing the function of complex neurocontrollers. High-dimensional FCA is shown to significantly improve on the accuracy of the basic analysis, to provide new insights concerning the main subsets of simple elements in the network that interact in a complex nonlinear manner, and to systematically reveal the types of interactions that characterize the evolved neurocontroller.

Artificial Intelligence↗