互作基因定位方法的研究和计算机软件的开发

质量性状中存在6种可能的基因互作类型, 即互补、重叠、累加、显性上位、隐性上位和抑制。在遗传研究中, 有时会遇到互作基因定位的问题, 但至今未见有关互作基因定位方法和计算机软件的系统的研究报道。文章给出了基于极大似然估计的互作基因定位方法及相应的计算机软件(IGMapping 1.0)。计算机模拟表明, 此方法可以无偏地估计一个共显性标记与一个互作基因之间的重组率或连锁距离。     

Automatic analysis of agarose gel images.

MOTIVATION: Automatic tools to speed up routine biological processes are very much sought after in bio-medical research. Much repetitive work in molecular biology, such as allele calling in genetic analysis, can be made semi-automatic or task specific automatic by using existing techniques from computer science and signal processing. Computerized analysis is reproducible and avoids various forms of human error. Semi-automatic techniques with an interactive check on the results speed up the analysis and reduce the error. RESULTS: We have successfully implemented an image processing software package to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in good quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactive checking to increase the accuracy of allele classification to 100%, the overall speed with which the data can be processed is greatly increased, compared to manual allele classification. AVAILABILITY: The IDL source code of the software is available on request from jonathan.flint@well.ox.ac.uk     

A low-cost procedure for automatic seafloor mapping, with particular reference to coral reef conservation in developing nations

Loss of marine biodiversity through benthic habitat destruction has created urgent needs for low-cost, high-performance seafloor survey methods. However, accurate seafloor mapping and classification is usually an expensive undertaking requiring sophisticated equipment, which excludes important low-budget user groups in developing nations. In this paper, we introduce a low-cost procedure for seafloor mapping based on free-of-charge data acquisition software that can be downloaded from the Internet. Using a Malaysian coral-reef case-study, we show how comprehensive bathymetric mapping can be implemented with such software using inexpensive eccosounder and GPS, and describe principles for integration of environmental data, either by connecting additional instruments to the computer (up to 32 instruments with up to eight channels each can be handled simultaneously), or by using simple synchronisation techniques with equipment that records to separate media, such as video cameras. We mapped a Malaysian coral-reef area of 114 hectares in 6 hours of video mapping, achieving reef mapping rates that matches rates currently achieved only with air-borne imaging devices. However, the present methodology results in completely ground-truthed data that can be classified according to many schemes by direct observation of the habitat, and provides detailed bathymetric data that satellite imagery or air-borne spectrographic sensors do not provide. The method can be used as a stand-alone reef mapping and classification tool on the scale of tens to hundreds of square kilometres. On larger scales (thousands of square kilometres), airborne survey methods are likely to remain more cost-effective than boat-based methods, yet also in such settings this simple method offer unprecedented capacity for ground truthing and thereby increased capacity for habitat classification.     

A selective mapping algorithm for computer analysis of voided urine cell images

One of the fundamental targets of the automated image analysis of cytologic preparations is the reduction of computer classification errors due to cells or other objects that do not lend themselves to image segmentation or that have morphologic features that may mislead the cell classification schemes. In prior work from this laboratory, the achievement of this goal was attempted by hierarchical analysis of sequential microscopic objects at high resolution. This paper reports on the successful development and implementation of an automated "selective mapping algorithm" that selects cells at low power for further analysis and eliminates a large proportion of unwanted "objects." The algorithm classifies the objects and extracts appropriate features from a 256 X 240 digital image obtained via a 10 X planachromatic objective. The five-node binary tree classifier used in this triage is described. The algorithm was trained and tested initially on 501 visually classified microscopic "objects," resulting in a correct acceptance rate of 61.3% and correct rejection rate of 81.3%. The selective mapping algorithm was subsequently integrated into the video-based image analysis system constructed at the Montefiore Medical Center for the diagnostic evaluation of sediments of voided urine. The algorithm was then tested on ten cytocentrifuge preparations for a preliminary evaluation of its performance. Up to 100 "objects" per case were selected by the algorithm for further classification by the computer at high power. Of the 810 "objects" selected by the selective mapping algorithm, 344 (42.5%) were classified by the computer at high resolution as cells of diagnostic value ("WELL" cells) and 466 were rejected.(ABSTRACT TRUNCATED AT 250 WORDS)     

Mapping Mediterranean maquis formations using Sentinel-2 time-series

Maquis, which provides numerous ecosystem services and constitutes an integral part of the Mediterranean ecosystem, is highly heterogeneous. However, despite its importance and heterogeneity, maquis is generally mapped as a single class, while forests are mapped for management purposes. Detailed mapping of the maquis formations is necessary to understand their ecology and manage them sustainably. This study presents a method that generates alliance-level maps of the maquis ecosystems through satellite images using various machine learning techniques with different feature combinations and evaluates the proposed approach in the Mediterranean region of Southern Turkey, which has an area of 95,000 km². Multi-temporal images extract information from vegetation phenology, while topographic and meteorological data are used to improve the classification. Cross-validation is performed using a ground-truth data set of approximately 7500 polygons. Results show that cost-effective and accurate maquis classification at the alliance level is possible using a combination of environmental features, multi-spectral, and multi-temporal satellite images. Adding environmental features to remotely sensed classification has improved the accuracy by 18%. The Random Forest (RF) algorithm improves classification accuracy by 7.3% and 14.6% relative to Support Vector Machine and Quadratic Discriminant Analysis algorithms, respectively. With the help of newly introduced features, we have succeeded in mapping 11 alliances with 64.2–82.7% overall accuracy. We believe the proposed classification approach will help improve the mapping of the shrubland ecosystems, which will significantly affect natural resource management, conservation, and adaptation to climate change.     

Computer-aided prediction of RNA secondary structures.

A brief survey of computer algorithms that have been developed to generate predictions of the secondary structures of RNA molecules is presented. Two particular methods are described in some detail. The first utilizes a thermodynamic energy minimization algorithm that takes into account the likelihood that short-range folding tends to be favored over long-range interactions. The second utilizes an interactive computer graphic modelling algorithm that enables the user to consider thermodynamic criteria as well as structural data obtained by nuclease susceptibility, chemical reactivity and phylogenetic studies. Examples of structures for prokaryotic 16S and 23S ribosomal RNAs, several eukaryotic 5S ribosomal RNAs and rabbit beta-globin messenger RNA are presented as case studies in order to describe the two techniques. Anm argument is made for integrating the two approaches presented in this paper, enabling the user to generate proposed structures using thermodynamic criteria, allowing interactive refinement of these structures through the application of experimentally derived data.     

Towards a taxonomy of Bacteria and Archaea based on interactive and cumulative data repositories

Taxonomy in the second decade of the 21st century is benefiting from technological advances in molecular microbiology, especially those related to genomics. Gene and genome databases are significantly increasing due to intense research activities in the field of molecular ecology and genomics. Taxa, and especially species, are tailored by means of the recognition of a phylogenetic, genomic and phenotypic coherence that reveal their uniqueness in the classification schema. Phylogenetic coherence is mainly revealed by means of 16S rRNA gene analyses for which curated databases such as EzTaxon and LTP provide a valuable tool for tree reconstruction to taxonomy users. On the other hand, in silico full or partial genomic sequence comparisons are called on to substitute cumbersome techniques such as DNA-DNA hybridization (DDH) to genomically circumscribe species. DDH similarity values around 70% would be equivalent to ANI values of 96%. Finally, finding an exclusive phenotypic property for the taxa to be classified is of paramount relevance to producing an operative and predictive classification system. The current methods used for taxonomic classification require significant laboratory experimentation, and generally will not produce interactive databases. The new high-throughput metabolomic technologies, such as ICR-FT and MALDI-TOF mass spectrometry methods, open the door to the construction of metabolic databases for taxonomic purposes. It is to be foreseen that, in the future, taxonomists will benefit significantly from public databases speeding up the classification process. However, serious effort will be needed to harmonize them and to prevent inaccurate material.     

Interactive NMR and computer simulation studies of lanthionine-ring structures

We report progress in elucidating the structure of nisin, a naturally occurring peptide antibiotic. Nisin contains five rings constrained by lanthionine or methyllanthionine bridges, as well as alpha, beta-unsaturated amino acids. We have determined conformations for two model compounds of ring A and a derivative of ring B through interactive nmr and computer simulation studies. High-resolution nmr techniques provides structural information, which was further refined through molecular dynamics simulations. These methods are being applied to the remaining constrained fragments of the molecule. This conformational information will be employed in an aufbau approach to determining the structure of the entire molecule.     

Use of computer simulations in microbial and molecular genetics

The development of five computer programs in microbial and molecular genetics is described. Four of these are simulations of genetic and physical mapping experiments, designed to give students experience in generating and analysing meaningful data, and to help in the consolidation of the concepts underlying the simulation. They should be used after the experiment proper has been performed, rather than as a substitute for it. The fifth is an interactive learning program on the genetic coding mechanism.     

Remote sensing imagery in vegetation mapping: a review

Aims Mapping vegetation through remotely sensed images involves various considerations, processes and techniques. Increasing availability of remotely sensed images due to the rapid advancement of remote sensing technology expands the horizon of our choices of imagery sources. Various sources of imagery are known for their differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for different purposes of vegetation mapping. Generally, it needs to develop a vegetation classification at first for classifying and mapping vegetation cover from remote sensed images either at a community level or species level. Then, correlations of the vegetation types (communities or species) within this classification system with discernible spectral characteristics of remote sensed imagery have to be identified. These spectral classes of the imagery are finally translated into the vegetation types in the image interpretation process, which is also called image processing. This paper presents an overview of how to use remote sensing imagery to classify and map vegetation cover.Methods Specifically, this paper focuses on the comparisons of popular remote sensing sensors, commonly adopted image processing methods and prevailing classification accuracy assessments.Important findings The basic concepts, available imagery sources and classification techniques of remote sensing imagery related to vegetation mapping were introduced, analyzed and compared. The advantages and limitations of using remote sensing imagery for vegetation cover mapping were provided to iterate the importance of thorough understanding of the related concepts and careful design of the technical procedures, which can be utilized to study vegetation cover from remote sensed images.     

Classification of immature and mature cells of the neutrophil series using morphometrical parameters

Quantitative morphological data of six classes of immature and mature cells of the neutrophil series of the bone marrow of normal persons were used for statistical classification experiments (myeloblasts, promyelocytes, myelocytes, metamyelocytes, bands and segments). On each cell, parameters were measured directly from the image or calculated from the shape of the density histogram or the counting densitogram using a Texture Analysis System (E. Leitz, Wetzlar, Germany). The parameters were analyzed with the interactive statistical pattern recognition system ISPAHAN. One half of the data were used as a learning set and the other half as the test set. The parameters were compared according to their performance in discrimination between the classes, alone and in combinations. Parameters not contributing to an improvement of the discrimination were disregarded. Eleven parameters were selected and used for classification by two different methods: a stepwise and a "one-shot" method. Stepwise classification resulted in a 79% correct classification rate. Most errors occurred between cell classes in neighboring stages of maturation. In 96% of all cases the computer classification was either in accordance with that of the technician or with a cell class of a neighboring maturation stage. One step classification by the computer was in agreement with the technicians in 82% of the cases. For 98% of the cells the computer classification was either in accordance with that of the technician or with a cell class of a neighboring maturation stage. The data set was collected by two technicians, operating independently. Differences in their interpretation of the maturation stage were found by comparing the performance of classifiers based on both cell samples. Since the images of the cells were not available for reexamination, the causes of disagreement in classification between the technicians and between computer and technicians could not be evaluated.     

Texture mapping: A new tool for molecular graphics

The real-time texture mapping capabilities of modern graphics workstations are explored with respect to their applications in a variety of relevant scenarios in interactive molecular modeling techniques. The common usage of texture mapping to reduce geometric complexity while enhancing realism is extended, opening new ways to visualize large amounts of molecular data in a comprehensive fashion. Thus, texture mapping may be employed to (1) display and filter multichannel information of structural properties on molecular surfaces, (2) improve the quality and accuracy of highly complex isodensity contours, (3) increase the rendering speed of space-filling atomic representations by two orders of magnitude and (4) apply volume-rendering techniques to large, three-dimensional density distributions in real time. Implementation of these novel techniques requires only moderate modifications or extensions to existing molecular modeling applications.     

Chromosomal assignment of 46 brain cDNAs.

Expressed sequence tags (ESTs) have been obtained from several hundred brain cDNAs as an initial effort to characterize expressed brain genes. These ESTs will become tools for human genome mapping and they will also provide candidate causative genes for inherited disorders affecting the central nervous system. We have developed a procedure for the rapid chromosomal assignment of these ESTs: cDNA sequences are first analyzed by a computer program to determine regions likely not to be interrupted by introns in the genomic DNA. A pair of oligonucleotide primers is then designed to amplify this region by the polymerase chain reaction using DNA template from human-rodent somatic cell hybrid chromosomal panels. The chromosomal assignment of the cDNA is determined by studying the segregation of the amplified products in these panels. In this paper we describe the mapping of 46 brain ESTs, as well as observations on the amplification of rodent sequences.     

经典植物分类学的发展与iFlora

简要介绍了经典植物分类的基础工作,即鉴定、描述、命名和分类,以及发展动向。作者认为计算机辅助鉴定（如delta intkey）将成为形态鉴定的常规手段;模式识别技术是植物图像鉴定的发展方向;突出物种遗传本质的分子鉴定将成为植物物种鉴定的核心。DELTA系统或类似的符合计算机逻辑的分类学描述语言将成为新一代植物志（iFlora）的基本语言。近20年来,一些学者逐渐表现出对现行植物命名法规的质疑和修改意愿,特别是生物法规草案（Draft BioCode）和谱系法规（PhyloCode）两个试行法规的诞生。它们促进对法规的革新与完善,并在iFlora中得以体现。以APG系统为代表的分子系统发育研究已经成为植物系统分类研究的主流,但在物种层面,物种的界定仅仅依靠分子信息显然是不够的,而必须运用综合的特征性状信息进行分析解读,真正实现物种在形态、遗传信息等综合性状的融合统一。了解和掌握这些新的技术和研究成果,无疑对于iFlora设计和编研有着重要的参考意义,而基于新技术和新理念的iFlora也将成为植物分类最新发展成果的集中体现。     

An Anchored Framework BAC Map of Mouse Chromosome 11 Assembled Using Multiplex Oligonucleotide Hybridization

Despite abundant library resources for many organisms, physical mapping of these organisms has been seriously limited due to lack of efficient library screening techniques. We have developed a highly efficient strategy for large-scale screening of genomic libraries based on multiplex oligonucleotide hybridization on high-density genomic filters. We have applied this strategy to generate a bacterial artificial chromosome (BAC) anchored map of mouse chromosome 11. Using the MIT mouse SSLP data, 320 pairs of oligonucleotide probes were designed with an “overgo” computer program that selects new primer sequences that avoid the microsatellite repeat. BACs identified by these probes are automatically anchored to the chromosome. Ninety-two percent of the probes identified positive clones from a 5.9-fold coverage mouse BAC library with an average of 7 positive clones per marker. An average of 4.2 clones was confirmed for 204 markers by PCR. Our data show that a large number of clones can be efficiently isolated from a large genomic library using this strategy with minimal effort. This strategy will have wide application for large-scale mapping and sequencing of human and other large genomes.     

An interactive technique for the display of nucleic acid secondary structure.

The ability to visualize nucleic acid secondary structure has become quite important since the advent of computer prediction and biochemical techniques that depict such structures. Manually drawing the conformations can be quite time consuming and tedious. Thus, the ability to draw with the aid of a computer the secondary structure of nucleic acid molecules is quite advantageous. This paper describes an interactive algorithm that permits one to generate such drawings which may then be used for further analysis and/or publications.     

Efficient interaction for automated chromosome analysis using asynchronous parallel processes.

It is likely that any practical automated chromosome analysis system will be interactive. To prevent long pauses in the stream of operator interactions, it is necessary, if using standard computer hardware, to configure for asynchronous and parallel operation. A system is presented which uses several computer processors, which can support one or more operators, and which divides processing into interactive and noninteractive sections, smoothes the rate of presentation of interactions, and keeps both the operator and the computer fully employed.     

大比例尺土壤保持服务制图分级方法研究

科学地编制生态系统服务空间分布图,有助于识别生态系统优先保护热点及空缺,能够为国土安全规划提供基础信息。但由于缺乏统一科学的生态系统服务分级方法,生态系统服务分布图的展示效果和制图效率都受到限制。不恰当的分级制图会误导决策者对生态系统服务空间分布特征的判断,增加生态保护决策的不确定性。以构建生态服务制图分级标准为目标,对我国6个典型县区的土壤保持服务数据展开1：25万比例尺制图分级案例研究。采用分级精度、面积均衡性、极差一致性、空间自相关一致性4个分级质量评价指标评价并比较了目前地图编制中常用的自然断点法、几何间隔法、累积比例法、等差法、分位数法5种分级算法的分级制图效果。结果表明,6个县区有相似的土壤保持服务分布特征：低值区覆盖面积大,高值区覆盖面积小。各县区土壤保持服务制图最优分级方法有差异：延庆区、丰满区最优分级方法为自然断点法;永靖县、天山区、安宁市最优分级方法为累积比例法;富阳区最优分级方法为几何间隔法。各分级方法中,累积比例法在6个县区综合制图效果最优或接近最优,适用性最好,能够较好的刻画各县区的土壤保持服务空间分布特征。本文提出的分级评价方法及其结果,可为生态系统土壤保持服务制图规范化和自动化提供科学依据。     

Object-oriented methods for habitat mapping at multiple scales – Case studies from Northern Germany and Wye Downs, UK

This paper presents an application of object-oriented techniques for habitat classification based on remotely sensed images and ancillary data. The study reports the results of habitat mapping at multiple scales using Earth Observation (EO) data at various spatial resolutions and multi temporal acquisition dates. We investigate the role of object texture and context in classification as well as the value of integrating knowledge from ancillary data sources. Habitat maps were produced at regional and local scales in two case studies; Schleswig-Holstein, Germany and Wye Downs, United Kingdom. At the regional scale, the main task was the development of a consistent object-oriented classification scheme that is transferable to satellite images for other years. This is demonstrated for a time series of Landsat TM/ETM+ scenes. At the local scale, investigations focus on the development of appropriate object-oriented rule networks for the detailed mapping of habitats, e.g. dry grasslands and wetlands using very high resolution satellite and airborne scanner images. The results are evaluated using statistical accuracy assessment and visual comparison with traditional field-based habitat maps. Whereas the application of traditional pixel-based classification result in a pixelised (salt and pepper) representation of land cover, the object-based classification technique result in solid habitat objects allowing easy integration into a vector-GIS for further analysis. The level of detail obtained at the local scale is comparable to that achieved by visual interpretation of aerial photographs or field-based mapping and also retains spatially explicit, fine scale information such as scrub encroachment or ecotone patterns within habitats.