HPS RESEARCH - DR. NELSON R. MANOHAR

Research Presentations

Data Mining Research

We are researching new (patent pending) approaches and computational bounds related to the family of related/inter-dependent problems in DNA sequence alignment with particular orientation towards the area of exploratory comparative genomics. These bioinformatic systems (herein referred to as "HPS DNA mining systems") on their own right constitute a significant and evolving body of bioinformatics research contributions and deliverables. More importantly, "HPS DNA mining systems" complete DNA mining tasks such as multiple (one-to-many, optimally) sequence alignment and (preliminary) phylogenetic searches within NEW AND LOWER RUN-TIME COMPLEXITY BOUNDS previously considered not feasible in practical cases and general use. For example, "HPS DNA mining systems" can find ALL matching instances of a DNA signature of size M within a sequence of size N in sub-linear time with respect to the input size (M+N) . That is, "HPS DNA mining systems" can perform (certain types of) COMBINATORIAL DATA MINING over sequences of large size N in SUB-LINEAR TIME! Moreover, unlike data mining alternatives based on heuristics, a strong theorethical framework underlies the optimization operating and search space of "HPS DNA mining systems". Moreover, the system not only aligns multiple sequences but it pinpoints with extraordinary precision in what ways do sequences (unearthed to be similar) differ while intrinsically remaining similar. That is, "HPS DNA mining systems" are not only capable of aligning multiple sequences but rather to construct a rating relationship of their (evolutionary) differences. Such capability allows "HPS DNA mining systems" to identify TRUE similarities between damaged, mutated, or evolutioned DNA sequences.

*** (a) ACCESS THE HPS DNA MINING SYSTEMS - PRELIMINARY REPORTS ***
(b) NON-TABBED VERSION

NOTE: THESE DOCUMENTS PRESENTS PRELIMINARY PATENT PENDING RESEARCH RESULTS; THEREFORE DISCLOSURE LEVEL IS PURPOSELY CURTAILED AND LIMITED. The findings here relate to a theoretical signal processing and data mining breakthrough, demonstrated herewith through its application to fundamental problems on the bioinformatics domain area. The following links provide access to reports with preliminary insigth into our research.

State Estimation Research

Dr. Manohar-Alers has threaded long-term research onto applied state estimation for random processes. This research introduces the Harmonic Process State (HPS) transform. Although the HPS Transform is particularly suited for adaptive process control, the results have VAST implications to other fields. In particular, important applications of the HPS Transform relate to feature extraction and data-mining. See Fig. for insight into the operation region of the HPS Transform. More importantly, the HPS Transform exhibits most desirable qualities on implementation ease, algorithmic complexity, computational stability, signal compressibility, decision-making robustness, information loss, and error behavior.

Adaptive Process Control Research

A motivating example: the structure of a distributed, loosely coupled, adaptive process control. A client C performs monitoring of a local resource R with sampling effort ║‹y(i)›║ but reports to a server S only on changes over a shared memory ‹π(k)›, thus exhibiting a reduction property ║k║ such being significantly less than ║i║.

About Dr. Manohar-Alers

Dr. Manohar-Alers' unique perspective has lead to novel and revolutionary approaches to important research problems. Dr. Manohar-Alers has shown a proven but growing skill set that coupled with precisely-honed insticts and plain hard work has often enabled him to compete with world-class specialists even when moving into new fields, areas, or domains. Dr. Manohar-Alers earned a B.S. in computer engineering in 1987. He also earned a M.S. computer engineering from the University of Wisconsin at Madison in 1988 and a M.S.E. in industrial engineering from the University of Michigan at Ann Arbor in 1992. Dr. Manohar-Alers earned his Ph.D. in computer science and engineering specializing in software systems research from the University of Michigan at Ann Arbor in 1997. Previously, he worked at the IBM T. J. Watson Research Center as a Research Staff Member and at AT&T Bell Laboratories (now Lucent Bell Labs) as a Member of the Technical Staff. His interests are in experimental software systems dealing with scalable systems theory, measurements, and resource management. He has been lead inventor in several patents on resource management. Previous research related to groupware, multimedia authoring, and advanced intelligent networks. He currently works as an independent researcher in Puerto Rico - USA. Dr. Manohar-Alers' credentials are found on his curriculum vitae. You may contact Dr. Manohar-Alers at nelsonmanohar@yahoo.com.

Our Assets

Dr. Manohar-Alers is currently unaffiliated to a research institution or grant. His body of research work has been done independently, in a self-supported manner, and thus readily available for use at his future research affiliation. His research work has the potential to produce high-impact (theoretical and applied) assets related to research publications, software, and patents of particular targeting toward valuable application domains such as life sciences, earth sciences, and information theory.

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