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Many properties of biological materials can be visualized directly using microscopy, electrophoresis, or other visualization mechanisms. The image subjects may have been improved before digital image capture using various detection-enhancement methods (such as stains, dyes, autoradiography, phase-contrast, interference microscopy, etc.) to visualize the data of interest. Digital image processing (see wikipedia.org Image RemovedImage Added and dictionary.com Image RemovedImage Added entries) is a method for the separation, detection, and quantification of the objects of interest in biological materials. Quantified data helps scientists perform more rigorous analyses of their biological experiments and improve the conclusions of their analyses.

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Dr. Richard Masland, M.D., the director of the National Institute of Neurological Disease and Blindness (NINDB), invited Lew to join the National Institutes of Health (NIH) in 1962. Lew was one of perhaps 20 neuropathologists in the country at the time. Later NINDB became the National Institute of Neurological Disorders and Stroke (NINDS). NINDB was looking for a neuropathologist for the Perinatal Research Branch (PRB) headed by Dr. Heinz Berendes, M.D. When he first came to NIH, Lew was determined to build something that implemented his ideas of mapping in biological images. He had an original LINC (Laboratory INstrument Computer created at MIT with NIH funding) computer at the time. Later, Lew upgraded this to a Digital Equipment Corporation Image RemovedImage Added (DEC) LINC-8 Image RemovedImage Added. The problem: he had a microscope and he had a computer. How could he combine the two?

The first thing he wanted to be able to do was move a slide via a computer-controlled microscope stage. Initially, he was going to do it with analog feedback. He talked to Wes Clark (who had helped build the LINC computer with Charlie Molner and others). Wes convinced Lew that he really wanted a digital stage - not an analog one - so that is what Lew developed: a series of stepping-motor-controlled stages that improved with each generation. The original design connected the stage with rubber bands, which was then greatly improved with direct stepping-motor drives. Lew had also been working with Russell Kirsch and Bill Watt from the National Bureau of Standards (NBS, now the National Institute of Standards and Technology or NIST Image RemovedImage Added). This early work involved describing biological images using computer picture grammars [1] that attempted to bring artificial intelligence and algorithmic methods to the description of biological images.

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The second computer-controlled microscope project was the NCI grain counter [2] that is discussed in its own section. Advancements in electronics technology enabled us to design the grain counter using high-speed shift-register memory chips to capture X,Y coordinates from a 10 frame/second non-interlaced TV system ( Imanco Quantimet 720 Image RemovedImage Added). Despite these advances, for larger image memories such as was needed for the RTPP, it would have been very difficult to implement image processing algorithms. This is because shift-register memory has delays in accessing any particular image pixel datum since the data must cycle around the circular shift register before the computer could access it. For complex algorithms with millions or billions of operations, this would be intolerable.

The culmination of these efforts was the Real Time Picture Processor (RTPP) described in journal papers [3, 4, 5, 6], as well as technical reports to be discussed and listed at the end of this history. We started this project just as the new Texas Instruments 4K bits X 1-bit dynamic RAMs (Random Access Memory - see history ofDRAM Image RemovedImage Added) became available. Their availability was discovered by George Carman who proceeded to design the RTPP using these new chips. Many skilled people made this project possible: the superb computer hardware architecture work by George and the mechanical engineering work by Sprague Hazard; the coming together of the right group of people, with synergistic skills who got along as a family, at the right time when the technology and the NIH's support resources were available; the NCI's Director Seymour Perry and administrator Bill Penland gave us crucial encouragement and financial support. Dr. Perry invited us to move to NCI as the Image Processing Unit (IPU) about 1972. In projects of this type, there is a window of time when the technology is appropriate for the job. Without the 4K dynamic RAMs, the RTPP would not have been possible. We were doing cutting-edge research, but a year or two later, charge-coupled devices would make their appearance and eventually make much of our design obsolete. But that is the nature of progress.

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One of the unique aspects of the RTPP was to implement the design as special-purpose parallel hardware with a flexible bus-architecture and a microcoded instruction set that reflected the types of operations routinely performed in image processing [3-4, TR-2, TR-7, TR-7a, TR-22]. Although other image processing computers were available, such as the ILLIAC-III Image RemovedImage Added, using a microcode architecture enabled an image processor to be constructed and built less expensively but with greater flexibility than building it entirely with discrete hardware. The special-purpose hardware could make real-time results possible (defined as reasonably fast enough to incorporate human feedback in tuning algorithms, such as interactively adjusting detection thresholds, etc.). A National Technical Information Service (NTIS)technical report [TR-7] describing the RTPP was one of the frequently requested reports one month as reported in their monthly newsletter for November 1976 under computer topics.

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• Lewis Lipkin, M.D., (mathematics and physical chemistry, and a neuropathologist), Head of the Image Processing Section (IPS); previously the (PRB, NINDB) and then the Image Processing Unit (IPU) in the NCI.
• Peter Lemkin, Ph.D. & M.S. EE, computer scientist and electrical engineer, IPS/NCI, and previously in (PRB, NINDB) and in IPU/NCI
• George Carman, M.S. EE, electrical engineer and computer hardware architecture, Technical Development Section (TDS), NINDB; Carman Engineering (now Lucidyne Corp Image RemovedImage Added).
• Morton Schultz, B.S. EE, electrical engineer, IPS/NCI, and previously in IPU/NCI
• Bruce Shapiro, Ph.D., B.S. math & physics, computer scientist, IPS/NCI, and previously in (PRB, NINDB),and in IPU/NCI
• Sprague Hazard, mechanical engineer (contractor consultant)
• Peter Kaiser, B.S. CS, computer scientist (IPU) in the NCI
• Earl Smith, M.S. CS, computer scientist (IPU) in the NCI
• Dan Kilgore, B.S. EE, computer programmer [Digital Equipment Corp Image RemovedImage Added (DEC) software engineer]
• Tom Duval and later Jim Camper, electronics technicians - helped construct the RTPP racks, and power-supplies cabinets
• Cambion Corporation, wire-wrapped the remaining 63 buffer memory boards and the back-planes

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Div
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Div class usa-width-one-half Div class usa-width-one-half Figure 3. The Digital Equipment Corporation DECsystem-2020 Image RemovedImage Added running the TOPS-10 Image RemovedImage Addedoperating system. The system is shown with Bruce Shapiro, holding a removable 180MB "bathtub" size disk pack (on the left), and Peter Lemkin (on the right). It had 512K words, 36-bits/word, 256K word virtual space/user, a very powerful instruction set, and many high-level computer languages, including SAIL (Stanford Artificial Intelligence Language - see wikipedia.org entry on SAIL) Image RemovedImage Added, that made implementing complex analysis algorithms much easier than on the PDP8e. SAIL was developed by Dan Swinehart and Bob Sproull of the Stanford AI Lab Image RemovedImage Added in 1970. Sproull was at Division of Computer Research and Technology (DCRT) in the early 1970s and introduced the language to DCRT [the precursor of NIH's Center for Information Technology (CIT)]. Over time, we implemented more of the advanced image processing and pattern recognition algorithms in SAIL, using the RTPP as a sophisticated data acquisition and interactive graphics front-end. Later many of these algorithms were rewritten in C and UNIX using X-windows (we rewrote the C/UNIX/X-windows GELLAB-II Image RemovedImage Added exploratory analysis system from the SAIL/TOPS-10/RTPP GELLAB-I), and in LISP (StructureLab with a Symbolics Lisp machine and later a Unix Platform) when the DECsystem-10/20 computer lines were phased out in favor of the VAX Image RemovedImage Addedcomputer lines. Later still, much of the C code for GELLAB-II was converted and rewritten in Java and used as part of the Open2Dprot Image RemovedImage Added project. We will discuss some of these projects later under the section Applications of the RTPP in Biomedical Research.

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The design of the RTPP was presented at the 1973 Asilomar Third Engineering Foundation Conference on Automated Cytology Image RemovedImage Added and published in 1974 [3-4]. This conference and a subsequent automated cytology workshop concentrated on the two solutions then available: image processing and pattern recognition of cell images, and the evolving field of flow cytometry. NIH was funding both fields. During this time we developed plans for integrating artificial intelligence techniques for understanding and analyzing biological materials and systems incorporating the RTPP, and these were also presented at the Asilomar workshop [5, TR-15].

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Not only did Cambion build the buffer memory boards, but using their standard technology, they also wired much of the backplanes. Their technology was an integrated system, and had been developed for rapid prototype construction in aerospace projects. It included cards, sockets, and racks. The system would not have worked had the parts been obtained from different vendors. By adapting Cambion's standards, we were able to take advantage of the reliability Cambion had developed for this kind of work. After Cambion created the boards and backplanes, our electronics technicians assembled them into several cabinets of 19" vertical racks including one cabinet for the power supplies. The buffer memories were 16 cards to a rack, with four racks. To avoid overheating, the cards were inserted in every other slot. Then the equipment was shipped to George in Oregon to finish construction and debugging. We had purchased a PDP8e for him to use in developing, debugging, and testing the interface. The computer was also critical for George to create various software tools to help manage the project. These included a wirewrap database program that could take pairs of (drawing #, chip #, pin #) triples that indicated a pair of wires to be connected using a technique called "wirewrap." This methodology was critical since a single buffer memory card was described in a large number of blueprints and it would be difficult to keep straight which pins connected to other pins in this complex global diagram. George then wrote additional software to translate these pairs to the standard lists that Cambion required. In a biomedical image processing and electronics conference, George's triple notation and his new way to handle the increasing complexity of multiple drawing wiring lists received a good reception from some of the developers of VHDL Image RemovedImage Added (a hardware description language). Because of space limitations, George put the PDP8e into a closet of his house with additional AC cooling. The PDP8e at that time cost more than his house. Today, the most inexpensive computers are many orders of magnitude more powerful than the PDP8e at a small fraction of their cost.

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The Axiomat was a dream microscope. (A photograph Image RemovedImage Added is available on Zeiss's microscope history Web page.) The microscope complex grew in the sense that as we wanted more and more control of the microscope functionality, we added it. In addition to control of the stage and control of the Z-axis, we also wanted control of the frequency of light that went through it. Although we experimented with various color selection methods, we settled for using interference filters. The RTPP and the microscope were controlled in real-time by a polling routine in BMON2 with the (X,Y,Z) direction control switches, A/Ds, and other states available for programs needing this data. Of course Lew Lipkin's pick-list idea was implemented and was part of BMON2.

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The software control program for the buffer memory I constructed on the PDP8e was called BMON2 (the Buffer Memory Monitor System) [40, TR-21, TR-21b, TR-23] and written in Fortran-II. BMON2, in addition to interfacing with the RTPP, also allowed running other programs to be batched to analyze the data. Given that the PDP8e had 32K words of memory, this was critical for doing complex sequential operations and for easily writing new RTPP applications. A Fortran-II library that could interface with the RTPP, BMOMNI [TR-23], allowed these other programs to access the RTPP as required. (See discussion on Fortran-II in the section on the grain counter. This shows the BMOMNI Fortran code.) BMON2 could capture and display images and do many image processing operations on the PDP8e. Another program called FLICKER [13] ran on the PDP8e and was used to analyze 2D gel images visually by alternately displaying one movable image on the video screen relative to another that was held in a constant screen position. Later, it allowed the comparison of two saved images as well. So a set of images could be compared against a reference sample. Some of the ideas on using flickering images to detect subtle differences in image matching were suggested by Bernice Lipkin, who is an expert in psychopictorics [41]. A third-generation version of FLICKER is available as open-source software at http://open2dprot.sourceforge.net/Flicker Image RemovedImage Added.

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Fortran-II source code of BMON2 and the image processing functions

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A Digital Equipment Corporation DECsystem-2020 Image RemovedImage Added was installed in the laboratory after we moved to the Park Building. We had been using the NIH's Division of Computer Research and Technology (DCRT) [now the Center for Information Technology (CIT)] DECsystem-10 time-shared system. As we used TOPS-10 operating system on the DECsystem-10, we installed TOPS-10 on the new DECsystem-2020. Bruce Shapiro had implemented a message-switching high-speed 9600-baud (normal speed was 300 or 1200 baud at the time) serial line multiplexor so we could move images and data to/from the DCRT system. However, the costs for the increasing amount of time we used on the DCRT system was escalating. For a cost comparable to renting time over a few years, we could purchase a dedicated system and have more compute power as well. So NCI supported us in purchasing the DECsystem-2020. This was a DEC Unibus system, which meant we could interface our hardware to this then-powerful 36-bit computer. In hindsight, this was one of the best procurements that Lew made. It offered us vastly better opportunities to interact with and manage the data that would not have been possible with a 9600 baud serial line. We could write software in the SAIL language, which meant we would have much more expressive power than we had with the PDP8e or PDP11 computers and could apply more advanced algorithms. This made a real difference in the productivity in analyzing real data with powerful algorithms.

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In addition to the RTPP, we acquired Comtal Image RemovedImage Added image processor systems that had Q-bus type PDP11 interfaces. These in turn were interfaced to a PDP11/40 computer that was connected to the DECsystem-2020 via software called SPIDER, a virtual device driver network. SPIDER allowed PDP11 computers to be accessed from the DECsystem2020 without writing a new DECsystem-2020 driver for each new PDP11 device. Bruce Shapiro, our expert on PDP11s, wrote a time-shared packet switcher on the PDP11/40 to connect PDP11 devices to this network. I wrote the device driver on the DECsystem-2020 to access these devices and make them available for DECsystem-2020 application software. Images acquired using the RTPP could be analyzed on the Comtals; Bruce used this to help analyze his nucleic acid electron micrographs.

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Many software analysis systems were developed using the RTPP, especially in the area of 2D gels with the GELLAB-I system [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,24, 25, 26, 27, 28, 29, 30, 31, 32], a 2D gel exploratory data analysis system integrating the image-processing with statistical databases for multiple samples (myself); and RNA electron micrographs of secondary structure [10, 11, 32, 39, 48, 49] (Bruce Shapiro). After the RTPP was decommissioned, GELLAB-I was redeveloped as a portable software system using Unix/C/X-windows and was called GELLAB-II [42, 43, 44, 45] (see Lemkin's History of GELLAB Image RemovedImage Added for more details, references, and history of GELLAB-II). Much of the work with GELLAB-I and GELLAB-II in exploratory data analysis led to its application to the DNA microarray domain (see http://maexplorer.sourceforge.net/ Image RemovedImage Added) MAExplorer []. A third-generation instantiation of this data-mining system is part of the Open2Dprot open-source project at http://open2dprot.sourceforge.net/ Image RemovedImage Added with the goal of extending proteomics data mining to 2D LC-MS, protein-arrays. Bruce went on to develop other RNA analysis software [35, 39, 47, 48, 49, 50], leading to the StructureLab project [50] and related RNA structure analysis (see his RNA structure research group Image RemovedImage Added).

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DesignDetails DesignDetails

Details on the RTPP Design

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Div
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Div class usa-width-one-half Div class usa-width-one-half Figure 4. The Real Time Picture Processor (RTPP) block diagram (reproduced with permission, from J. Histochem. Cytochem. [4], 1974). This shows additional parts of the system including a PDP11/20 message switcher to a PDP-10 Artificial Intelligence system PRDL (PRocedural Description Language) [5, TR-15] originally being developed on NIH's DCRT (now CIT) PDP-10 facility. The early microscope also had a 1024x1024 8-bit galvanometer scanner that could be used in place of the Quantimet 720 scanner. The later microscope was built around a Zeiss Axiomat microscope. An early high-quality grayscale display (Dicomed 31) was also used to make high-quality display images. Its functionality was replaced by the Quantimet grayscale buffer-memory display. The PDP8e accessed the RTPP using the BMON2 software [40, TR-21b]. The PDP-10 multiprocessor KL-10 system was a shared time-share computer at DCRT (now CIT). This was replaced in our design by a dedicated DECsystem-2020 when it became more cost-effective to have a dedicated computer. The DECsystem-2020 was a new microcoded processor that DEC was able to build for a fraction of the cost of the PDP-10. The PRDL [TR-15] and PROC10 [TR-8] image processing software were created to interface with the RTPP. We had considered creating a MAINSAIL(R) Image RemovedImage Added compiler for use with the GPPASM (GPP assembler program) [TR-16] so that we could program the GPP in a SAIL-like language only available on large PDP-10 class systems. Later, a light box for films was used with the Quantimet vidicon scanner (see Figure 18) with changeable 35mm lenses (not shown in this block diagram - see Figure 5) to scan autoradiograph and wet 2D gels, RNA electron micrographs, and other transparencies.

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During this time, we had the conviction, led by Lew Lipkin and George Carman, that anything that we wanted to be do in software could be done by a series of sequential gates. These could be proved Boolean algebraically correct using Karnaugh Maps Image RemovedImage Added, hardware finite state machines, and related techniques. George had just taken a microprogramming design course as part of his masters degree in computer hardware architecture and the design of buffer memories and the General Picture Processor (GPP) were perfect test beds in which to try out these new design principles which were relatively new for projects like this. Some of the design diagrams are shown in Figures 11 through 14 (from the Carman [4] paper). Figure 15 shows some examples of GPP microprogrammed instructions for manipulating the buffer memory data. The design was further described in some of the technical reports [TR-7, TR-7a, TR-16, TR-21, TR-21b, TR-22] listed at the end of this history. Because we were prototyping the system, the card was constructed using wire wrapping rather than multilayer printed circuit boards. A commercial version would have used printed circuit boards, but would only have been economically feasible if many copies of the RTPP were produced. Using complex multi-level printed circuit boards is generally too expensive for a research lab. 

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BufferMemoryBoard BufferMemoryBoard

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Fig-RTPP-Examples-of-GPASM-code Fig-RTPP-Examples-of-GPASM-code

Figure 15. The Examples of RTPP instructions for the GPP (reproduced with permission from J. Histochem. Cytochem. [4], 1974). The Pi refers to a 3x3 pixel neighborhood that would be tessellated through the entire image. The GPP instructions [A HREF="#TR-22">TR-22] could be compiled by the GPPASM [A HREF="#TR-16">TR-16] assembler program running on the PDP8e and then loaded into the GPP instruction memory. A debugger for the GPP was DDTG that ran on the PDP8e [A HREF="#TR-2">TR-2] but controlled the GPP and buffer memories. We had also been evaluating collaborating on the construction of a MAINSAIL(R) Image RemovedImage Added compiler to generate GPP assembly code so we could program the RTPP in a SAIL-like language.

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Eric painstakingly generated paired data for about 1,400 spots from the segmented images and their paired spot lists for a few gels. Because of the difficulty in matching or pairing spots between gels, I also developed spot-pairing and spot "landmarking" programs, which ran interactively on the RTPP/PDP8e. (Landmarking is visually identifying a set of spots that are common in both the reference gel and each additional gel sample so spot pairing could proceed.) Eric then subjected the data to SPSS Image RemovedImage Addedstatistical analysis with encouraging results (t-Tests, Spearman correlation, ANOVA) and it was published in [14] and enhancements in [15,18-21]. All three of these programs were rewritten in SAIL for the DECsystem-2020. At this point we realized that we wanted to build a database containing large numbers of gels to detect marker proteins or classify samples by protein pattern signatures indicating states of differentiation, disease conditions, or other experimental conditions. This was the basis of GELLAB-I.

This led to the SAIL program CGELP, in GELLAB-I, to construct a composite gel database with a virtual reference gel [14-18,20,30] and the addition of many more statistical methods. (The subsequent Unix version was called CGELP2 [30, 42, 43, 44, 45] where additional statistical exploratory data analysis methods were added - see [history of GELLAB Image RemovedImage Added].) Spots of a set of N-1 gels would be matched to one of the gels called a reference gel and spots missing in the physical reference gel would be extrapolated into the reference gel. Figure 19 shows the reference gel 324.1 that was an acute myeloid leukemia (AML) gel, scanned with the RTPP. This reference gel was used in many of the leukemia databases to tie the data together [14, 15, 16, 17, 18, 22]. The collection of SAIL programs, as well as their RTPP interface, was called GELLAB-I. After leaving NIH (for the University of Chicago), Eric would fly back to work in our laboratory to do marathon late-night landmarking sessions to help generate these databases of large numbers of 2D leukemia gels. Over the years, we had built various databases with over 400 gel samples. The leukemia database had over 130 samples. Some of these gel sample images are available on the bioinformatics.org/lecb2dgeldb Image RemovedImage Added open source repository. This early research led to my interest in exploratory data analysis and future work with microarrays with MAExplorer.sourceforge.net Image RemovedImage Added [46], and proteomics exploratory data analysis using open2dprot.sourceforge.net Image RemovedImage Added.

Peter Sonderegger, while a post-doc at the National Institute of Child Health and Development (NICHD), used the GELLAB-I system with the RTPP to investigate how the expression of axonal proteins of sensory and motor neurons was influenced by non-neuronal cells [27, 29, 45]. At the same time we were investigating the feasibility of porting GELLAB-I (written in SAIL) to the PASCAL computer language. The inflexibility of PASCAL eventually led us to convert GELLAB-I to the portable C/UNIX/X-windows environment called GELLAB-II [42, 43, 44, 45] The DECsystem-10 SAIL version, GELLAB-I, was exported to research labs at Univ. of Chicago (Eric Lester) and Univ. of Kiel (Heinz Busse). The Unix version, GELLAB-II, was exported to a number of research labs around the world (CDC with Jim Myrick [44], Univ. Zurich with Peter Sonderegger, Agr. Univ. Norway with Trygve Krekling, and others) and led to a commercial subset version for Windows PCs called GELLAB-II++ by CSPI/Scanalytics.

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Heme-AML-2Dgel-Lester Heme-AML-2Dgel-Lester

Figure 19. One of the early 2-dimensional (2D) gels scanned with the vidicon/RTPP system (leukemia AML sample number 324.1 - a 2D-gel autoradiograph scanned to a 512x512 8-bit image) in a collaboration with Eric Lester (NCI oncologist at the time), Lewis Lipkin, and myself with the GELLAB-I system [14, 15, 16, 17, 18, 22]. The film was scanned on a light box (shown in Figure 18 above) along with a neutral-density step wedge at the top so the grayscale image data could be mapped to optical density, resulting in a more linear calibration with protein concentration in the 2D gel. The leukemia gels are part of a public 2D gel database at http://bioinformatics.org/lecb2dgeldb Image RemovedImage Added.

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Use of the RTPP for RNA secondary structure analysis

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   Lipkin, L.E., Watt, W.C., Kirsch, R.A.: The analysis, synthesis, and description of biological images. Ann N Y Acad Sci. 128(3): 984-1012, 1966.

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   Lipkin74 Lipkin74

   Lipkin, L.E., Lemkin, P.F., Carman, G.: Automated autoradiographic grain counting in human determined context. J. Histochem. Cytochem. 22(7): 755-765, 1974. (PDF Image RemovedImage Added)

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   RTPP-JHC-I-paper RTPP-JHC-I-paper

   Lemkin, P.F., Carman, G., Lipkin, L., Shapiro, B., Schultz, M., Kaiser, P.: A real time picture processor for use in biologic cell identification. I. System design. J. Histochem. Cytochem. 22(7): 725-731, 1974. (PDF Image RemovedImage Added)

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   Carman, G., Lemkin, P.F., Lipkin, L., Shapiro, B., Schultz, M., Kaiser, P.: A real time picture processor for use in biologic cell identification. II. Hardware implementation. J. Histochem. Cytochem. 22(7): 732-740, 1974. (PDF Image RemovedImage Added)

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   Shapiro, B., Lemkin, P.F., Lipkin, L.: The application of artificial intelligence techniques to biologic cell identification. J. Histochem. Cytochem. 22(7): 741-750, 1974. (PDF Image RemovedImage Added)

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   Schultz, M.L., Lipkin, L.E., Wade, M.J., Lemkin, P.F., Carman, G.M.: High resolution shading correction. J. Histochem. Cytochem.22(7): 751-754, 1974. (PDF Image RemovedImage Added)

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   Shapiro, H.M., Bryan, S.D., Lipkin, L.E., Stein, P.G., Lemkin, P.F.: Computer-aided microspectrophotometry of biological specimens. Exp Cell Res. 67(1): 81-89, 1971.

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   Lemkin, P.F.: The boundary trace transform: An edge and region enhancement transform. Comp. Graphics Image Processing 9: 150-165, 1979.

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   Lemkin, P.F., Lipkin, L., Merril, C., Shiffrin, S.: Protein abnormalities in macrophages bearing asbestos. Environ. Health Perspect. 34: 5-89, 1980. (PDF)

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    Lipkin, L.E.: Cellular effects of asbestos and other fibers: correlations with in vivo induction of pleural sarcoma. Environ. Health Perspect. 34:91-102, 1980. (PDF)

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    Lemkin79b Lemkin79b

    Lemkin, P.F.: An approach to region splitting. Comp. Graphics Image Processing 10: 281-288, 1979.

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    Lemkin79c Lemkin79c

    Lemkin, P.F., Lipkin, L.: Use of the positive difference transform for RBC elimination in bone marrow smear images. Anal. Quant. Cytol. 1(1): 67-76, 1979.

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    Lemkin79d Lemkin79d

    Lemkin, P.F., Merril, C., Lipkin, L., Van Keuren, M., Oertel, W., Shapiro, B., Wade, M., Schultz, M., Smith, E.: Software aids for the analysis of 2D gel electrophoresis images. Comput. Biomed. Res. 12: 517-544, 1979.

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    Lemkin80c Lemkin80c

    Lester, E.P., Lemkin, P.F., Cooper, H.L., Lipkin, L.E.: Computer-assisted analysis of two-dimensional electrophoresis of human peripheral blood lymphocytes. Clin. Chem. 26: 1392-1402, 1980. (PDF Image RemovedImage Added)

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    Lipkin, L.E., Lemkin, P.F.: Data base techniques for multiple PAGE (2D gel) analysis. Clin. Chem. 26: 1403-1413, 1980. (PDF Image RemovedImage Added)

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    Lemkin81a Lemkin81a

    Lemkin, P.F., Lipkin, L.: GELLAB: A computer system for 2D gel electrophoresis analysis. I. Segmentation and preliminaries. Comput. Biomed. Res. 14: 272-297, 1981.

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    Lemkin81b Lemkin81b

    Lemkin, P.F., Lipkin, L.: GELLAB: A computer system for 2D gel electrophoresis analysis. II. Spot pairing. Comput. Biomed. Res. 14: 355-380, 1981.

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    Lemkin, P.F., Lipkin, L.: GELLAB: A computer system for 2D gel electrophoresis analysis. III. Multiple gel analysis. Comput. Biomed. Res. 14: 407-446, 1981.

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    Lemkin81d Lemkin81d

    Lester, E.P., Lemkin, P.F., Lipkin, L.E.: New dimensions in protein analysis - 2D gels coming of age through Image Processing. Anal. Chem. 53: 390A-397A, 1981.

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    Lester, E.P., Lemkin, P.F., Lipkin, L.E., Cooper, H.L.: A two-dimensional electrophoretic analysis of protein synthesis in resting and growing lymphocytes in vitro. J. Immunol. 126: 1428-1434, 1981.

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    Lemkin, P.F., Lipkin, L.E., Lester, E.P.: Some extensions to the GELLAB 2D electrophoresis gel analysis system. Clin. Chem. 28: 840-849, 1982. (PDF Image RemovedImage Added)

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    Lester82a Lester82a

    Lester, E.P., Lemkin, P.F., Lipkin, L.E.: A two-dimensional gel analysis of autologous T and B lymphoblastoid cell lines. Clin. Chem.28: 828-839, 1982. (PDF Image RemovedImage Added)

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    Lester, E.P., Lemkin, P.F., Lowery, J.F., Lipkin, L.E.: Human leukemias: A preliminary 2D electrophoretic analysis. Electrophoresis 3: 364-375, 1982.

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    Howard, R.J., Aley, S.B., Lemkin, P.F.: High resolution comparison of Plasmodium Knowlesi clones of different variant antigen phenotypes by 2D gel electrophoresis and computer analysis. Electrophoresis 4: 420-427, 1983.

25. Anchor
    Lemkin83a Lemkin83a

    Lemkin, P.F., Lipkin, L.E.: 2D Electrophoresis gel data base analysis: Aspects of data structures and search strategies in GELLAB. Electrophoresis 4: 71-81, 1983.

26. Anchor
    Lester83a Lester83a

    Lester, E.P., Lemkin, P.F., Lipkin, L.E.: States of differentiation in leukemias: A 2D gel analysis. In Rowley, J. D. and Ultmann, J. E. (Eds.): Proceedings of 5th Annual Bristol Myers Symposium on Cancer Research. Chromosomes and Cancer: From Molecules to Man. New York, Academic Press, 1983, pp. 226-245.

27. Anchor
    Lemkin84a Lemkin84a

    Lemkin, P.F., Sonderegger, P., Lipkin, L.: Identification of coordinate pairs of polypeptides: A technique for screening of putative precursor product pairs in 2D gels.Clin. Chem. 30: 1965-1971, 1984. (PDF Image RemovedImage Added)

28. Anchor
    Lester84a Lester84a

    Lester, E.P., Lemkin, P F., Lipkin, L.E.: Protein indexing in leukemias and lymphomas. Ann. N.Y. Acad. Sci. 428: 158-172, 1984.

29. Anchor
    Sonderegger85 Sonderegger85

    Sonderegger, P., Lemkin, P.F., Lipkin, L., Nelson, P.: Differential modulation of the expression of axonal proteins by non-neuronal cells and the peripheral and central nervous system. EMBO J. 4: 1395-1401, 1985. (PDF)

30. Anchor
    Lemkin81f Lemkin81f

    Lemkin, P.F., Lipkin, L.E.: GELLAB: Multiple 2D electrophoretic gel analysis. In Allen, R. and Arnaud (Eds.): Electrophoresis '81. New York, W. De Gruyter, 1981, pp. 401-411.

31. Anchor
    Lemkin83b Lemkin83b

    Lemkin, P.F. , Lipkin, L.E.: Database techniques for 2D electrophoretic gel analysis. In Geisow, M. and Barrett, A. (Eds.): Computing in Biological Science. North Holland, Elsevier, 1983, pp. 181-226.

32. Anchor
    Lester84a Lester84a

    Lester, E.P., Lemkin, P.F.: A 'GELLAB' computer assisted 2D gel analysis of states of differentiation in hematopoietic cells. In Neuhoff, V. (Ed.): Electrophoresis '84. Chemie, Springer-Verlag, 1984, pp. 309-311.

33. Anchor
    Lemkin79d Lemkin79d

    Lemkin, P.F., Shapiro, B., Lipkin, L., Maizel, J., Sklansky, J., Schultz, M.: Preprocessing of electron micrographs of nucleic acid molecules for automatic analysis by computer. II. Noise removal and gap filling. Comput. Biomed. Res. 12: 615-630, 1979.

34. Anchor
    Lipkin79b Lipkin79b

    Lipkin, L., Lemkin, P.F., Shapiro, B., Sklansky, J.: Preprocessing of electron micrographs of nucleic acid molecules for automatic analysis by computer. Comput. Biomed. Res. 12: 279-289, 1979.

35. Anchor
    Shapiro77a Shapiro77a

    Shapiro, B., Lipkin L.: The circle transform, an articulable shape descriptor. Comput. Biomed. Res. 10: 511-28, 1977.

36. Anchor
    Shapiro77b Shapiro77b

    Shapiro, B.: Language processor generation with BNF inputs: methods and implementation. Comp. Programs. Biomedicine 7:85-98, 1977.

37. Anchor
    Shapiro79a Shapiro79a

    Shapiro, B., Pisa, J., Sklansky, J.: Skeletons from sequential boundary data. Proc. Intl. Conf. On Pattern Recognition and Image Processing. IEEE Comp. Soc. Press, Los Angeles, CA., 265-270, 1979.

38. Anchor
    Shapiro81a Shapiro81a

    Shapiro, B., Pisa, J., Sklansky, J.: Skeleton generation from xy boundary sequences. Comp. Vision Graphics Image Processing 15(2) 136-153, 1981.

39. Anchor
    Shapiro79b Shapiro79b

    Shapiro, B.S., Lipkin, L.E., Maizel, J.V.: Computerized generation of secondary structure maps for nucleic acids. Comp. Biomed. Res.12(6):545-568, 1979.

40. Anchor
    BMON2-CPIB-paper BMON2-CPIB-paper

    Lemkin, P.F., Lipkin, L.: BMON2 - A distributed monitor system for biological image processing. Computer Programs in Biomedicine 11: 21-42, 1980. (PDF)Reprinted from COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, Vol 11, Lemkin PD and LipkinL, BMON2 - A distributed monitor system for biological image processing, Pages 21-42, Copyright (1980), with permission from Elsevier.

41. Anchor
    Lipkin70 Lipkin70

    Lipkin, B.S., Rosenfeld, A. (Eds): Picture Processing and Psychopictorics. Academic Press, New York, 1970, pps 526.

42. Anchor
    Lipkin89g Lipkin89g

    Lemkin, P.F.: GELLAB-II: A workstation based 2D electrophoresis gel analysis system. In Endler, T. and Hanash, S. (Eds.): Proceedings of 2D Electrophoresis. West Germany, VCH Press, 1989, pp. 52-57. (This was the announcement of GELLAB-II)

43. Anchor
    Lipkin89h Lipkin89h

    Lemkin, P.F., Lester, E.P.: Database and search techniques for 2D gel protein data: A comparison of paradigms for exploratory data analysis and prospects for biological modeling. Electrophoresis 10(2): 122-140, 1989.

44. Anchor
    Robinson95 Robinson95

    Robinson, M.K., Myrick, J.E., Henderson, L.O., Coles, C.D., Powell, M.K., Orr, G.A., Lemkin, P.F.: Two-dimensional protein electrophoresis and multiple hypothesis testing to detect potential serum protein biomarkers in children with fetal alcohol syndrome. Electrophoresis 16: 1176-1183, 1995.

45. Anchor
    Stoeckli89 Stoeckli89

    Stoeckli, E.T., Lemkin, P.F., Kuhn, T.B., Ruegg, M.A., Heller, M., Sonderegger, P.: Identification of proteins secreted from axons of embryonic dorsal-root-ganglia neurons. Eur. J. Biochem. 180: 249-258, 1989.

46. Anchor
    Lemkin00a Lemkin00a

    Lemkin, P.F., Thornwall, G., Walton, K., Hennighausen, L: The Microarray Explorer tool for data mining of cDNA microarrays - application for the mammary gland, Nucleic Acids Res. 20(22): 4452-4459, 2000.

47. Anchor
    Shapiro88 Shapiro88

    Shapiro, B.A.: An algorithm for comparing multiple RNA secondary structures. Comput. Appl. Biosci. 4(3): 387-393, 1988.

48. Anchor
    Margalit89 Margalit89

    Margalit, H., Shapiro, B.A., Oppenheim, A.B., Maizel, J.V. Jr.: Detection of common motifs in RNA secondary structures. Nucleic Acids Res. 17(12): 4829-4845, 1989.

49. Anchor
    Le89 Le89

    Le, S.Y., Owens, J., Nussinov, R., Chen, J.H., Shapiro, B., Maizel, J.V.: RNA secondary structures: comparison and determination of frequently recurring substructures by consensus. Comput. Appl. Biosci. 5(3): 205-210, 1989.

50. Anchor
    Shapiro96 Shapiro96

    Shapiro, B.A., Kasprzak, W.: STRUCTURELAB: a heterogeneous bioinformatics system for RNA structure analysis. J Mol. Graph.14(4): 194-205, 222-224, 1996.

...

Peter F. Lemkin, Lemkingroup.com Image RemovedImage Added

(Note: You may also access the PDF and journal articles on the lemkingroup.com RTTP history mirror Image RemovedImage Added.)
Original: 02/25/2007, Version #57 - original released to History of NIH
Revised: 9/5/2011, Version: #59 - fixed missing links and navigation change
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